" Im not Racist but...": Discovering Bias in the Internal Knowledge of Large Language Models.
Salinas, A.; Penafiel, L.; McCormack, R.; and Morstatter, F.
arXiv preprint arXiv:2310.08780. 2023.
link
bibtex
@article{salinas2023not,
title={" Im not Racist but...": Discovering Bias in the Internal Knowledge of Large Language Models},
author={Salinas, Abel and Penafiel, Louis and McCormack, Robert and Morstatter, Fred},
journal={arXiv preprint arXiv:2310.08780},
year={2023}
}
A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment.
Xie, H.; Zhu, J.; Khayatkhoei, M.; Li, J.; Hussein, M. E.; and Abdalmageed, W.
In
Proceedings of the 40th International Conference on Machine Learning, volume 202, pages 38258–38271, July 2023. PMLR
![A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment [pdf]](//bibbase.org/img/filetypes/pdf.svg "paper")
paper
![A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment [link]](//bibbase.org/img/filetypes/link.svg "link")
link
link
bibtex
@InProceedings{xie2023critical-view-dynamics,
title={A Critical View of Vision-Based Long-Term Dynamics Prediction Under Environment Misalignment},
author={Xie, Hanchen and Zhu, Jiageng and Khayatkhoei, Mahyar and Li, Jiazhi and Hussein, Mohamed E. and Abdalmageed, Wael},
booktitle={Proceedings of the 40th International Conference on Machine Learning},
pages={38258--38271},
year={2023},
month={July},
volume={202},
publisher={PMLR},
url_Paper={https://arxiv.org/pdf/2305.07648.pdf},
url_Link={https://icml.cc/virtual/2023/poster/23866},
ISIArea = {ML, VISTA}
}
A Data Fusion Framework for Multi-Domain Morality Learning.
Guo, S.; Mokhberian, N.; and Lerman, K.
CoRR, abs/2304.02144. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2304-02144,
author = {Siyi Guo and
Negar Mokhberian and
Kristina Lerman},
title = {A Data Fusion Framework for Multi-Domain Morality Learning},
journal = {CoRR},
volume = {abs/2304.02144},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2304.02144},
doi = {10.48550/ARXIV.2304.02144},
eprinttype = {arXiv},
eprint = {2304.02144},
timestamp = {Mon, 17 Apr 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2304-02144.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
A Dynamic Residual Learning Approach to Improve Physics-Constrained Neural Network Predictions in Unconventional Reservoirs.
Mohd Razak, S.; Cornelio, J.; Cho, Y.; Liu, H.; Vaidya, R.; and Jafarpour, B.
In
Middle East Oil, Gas and Geosciences Show, 2023. OnePetro
Paper
link
bibtex
@inproceedings{mohd_razak_dynamic_2023-1,
title = {A {Dynamic} {Residual} {Learning} {Approach} to {Improve} {Physics}-{Constrained} {Neural} {Network} {Predictions} in {Unconventional} {Reservoirs}},
url = {https://onepetro.org/SPEMEOS/proceedings/23MEOS/D021S084R005/517253},
urldate = {2024-02-12},
booktitle = {Middle {East} {Oil}, {Gas} and {Geosciences} {Show}},
publisher = {OnePetro},
author = {Mohd Razak, Syamil and Cornelio, Jodel and Cho, Young and Liu, Hui-Hai and Vaidya, Ravimadhav and Jafarpour, Behnam},
year = {2023},
}
A FastMap-Based Framework for Efficiently Computing Top-K Projected Centrality.
Li, A.; Stuckey, P.; Koenig, S.; and Thittamaranahalli, S.
Proceedings of the Ninth International Conference on Machine Learning, Optimization, and Data Science (LOD-2023). 2023.
link
bibtex
@article{tksk08,
author={Ang Li and Peter Stuckey and Sven Koenig and Satish Thittamaranahalli},
title={A FastMap-Based Framework for Efficiently Computing Top-K Projected Centrality},
journal={Proceedings of the Ninth International Conference on Machine Learning, Optimization, and Data Science (LOD-2023)},
year={2023}
}
A Framework for Broad Dissemination of Hydrological Models to Non-Expert Users.
Schaffhauser, T.; Garijo, D.; Osorio, M.; Bittner, D.; Pierce, S.; Vargas, H.; Disse, M.; and Gil, Y.
Computers and Geosciences. 2023.
link
bibtex
@article{schaffhauser-etal-cgj23,
title = {A Framework for Broad Dissemination of Hydrological Models to Non-Expert Users},
author = {Timo Schaffhauser and Daniel Garijo and Maximiliano Osorio and Daniel Bittner and Suzanne Pierce and Hernan Vargas and Markus Disse and Yolanda Gil},
journal = {Computers and Geosciences},
year = {2023}
}
A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain.
Kejriwal, M.; Haidarian, H.; Chiu, M.; Xiang, A.; Shrestha, D.; and Javed, F.
arXiv preprint arXiv:2310.05258. 2023.
link
bibtex
@article{kejriwal2023knowledge,
title={A Knowledge Graph-Based Search Engine for Robustly Finding Doctors and Locations in the Healthcare Domain},
author={Kejriwal, Mayank and Haidarian, Hamid and Chiu, Min-Hsueh and Xiang, Andy and Shrestha, Deep and Javed, Faizan},
journal={arXiv preprint arXiv:2310.05258},
year={2023}
}
A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning.
Tang, Z.; and Kejriwal, M.
arXiv e-prints,arXiv–2302. 2023.
link
bibtex
@article{tang2023pilot,
title={A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning},
author={Tang, Zhisheng and Kejriwal, Mayank},
journal={arXiv e-prints},
pages={arXiv--2302},
year={2023}
}
A Study of Distance Functions in FastMapSVM for Classifying Seismograms.
Sharma, K.; Li, A.; White, M.; and Thittamaranahalli, S.
Proceedings of the Twenty-Second International Conference on Machine Learning and Applications (ICMLA-2023). 2023.
link
bibtex
@article{tksk11,
author={Kushal Sharma and Ang Li and Malcolm White and Satish Thittamaranahalli},
title={A Study of Distance Functions in FastMapSVM for Classifying Seismograms},
journal={Proceedings of the Twenty-Second International Conference on Machine Learning and Applications (ICMLA-2023)},
year={2023}
}
A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense.
Santos, H.; Shen, K.; Mulvehill, A. M; Kejriwal, M.; and McGuinness, D. L
Data Intelligence,1–29. 2023.
link
bibtex
@article{santos2023theoretically,
title={A Theoretically Grounded Question Answering Data Set for Evaluating Machine Common Sense},
author={Santos, Henrique and Shen, Ke and Mulvehill, Alice M and Kejriwal, Mayank and McGuinness, Deborah L},
journal={Data Intelligence},
pages={1--29},
year={2023},
publisher={MIT Press One Rogers Street, Cambridge, MA 02142-1209, USA journals-info~…}
}
A structural study of Big Tech firm-switching of inventors in the post-recession era.
Sun, Y.; and Kejriwal, M.
2023.
link
bibtex
@misc{sun2023structural,
title={A structural study of Big Tech firm-switching of inventors in the post-recession era},
author={Yidan Sun and Mayank Kejriwal},
year={2023},
eprint={2307.07920},
archivePrefix={arXiv},
primaryClass={cs.SI}
}
ACCESS Pegasus: Bringing Workflows to the ACCESS Masses.
Rynge, M.; Vahi, K.; Alam, M. Z.; Deelman, E.; Miller, T.; Livny, M.; Knuth, S.; Griffioen, J.; Goodhue, J.; Hudak, D.; Ma, J.; Pasquale, A.; and Fein, L.
In
Practice and Experience in Advanced Research Computing, of
PEARC '23, pages 478–480, New York, NY, USA, 2023. Association for Computing Machinery
Paper
doi
link
bibtex
@InProceedings{ rynge-pearc-2023,
Author = {Rynge, Mats and Vahi, Karan and Alam, Mohammad Zaiyan and
Deelman, Ewa and Miller, Todd and Livny, Miron and Knuth,
Shelley and Griffioen, James and Goodhue, John and Hudak,
David and Ma, Julie and Pasquale, Andrew and Fein, Lissie},
Title = {ACCESS Pegasus: Bringing Workflows to the ACCESS Masses},
Year = {2023},
ISBN = {9781450399852},
Publisher = {Association for Computing Machinery},
Address = {New York, NY, USA},
URL = {https://doi.org/10.1145/3569951.3597590},
DOI = {10.1145/3569951.3597590},
BookTitle = {Practice and Experience in Advanced Research Computing},
Pages = {478–480},
numpages = {3},
Location = {Portland, OR, USA},
Series = {PEARC '23}
}
ACQUIRED: A Dataset for Answering Counterfactual Questions In Real-Life Videos.
Wu, T.; Dou, Z.; Hu, Q.; Hou, Y.; Chandra, N.; Freedman, M.; Weischedel, R.; and Peng, N.
In Bouamor, H.; Pino, J.; and Bali, K., editor(s),
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 11753–11770, Singapore, December 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
@inproceedings{wu-etal-2023-acquired,
title = "{ACQUIRED}: A Dataset for Answering Counterfactual Questions In Real-Life Videos",
author = "Wu, Te-Lin and
Dou, Zi-Yi and
Hu, Qingyuan and
Hou, Yu and
Chandra, Nischal and
Freedman, Marjorie and
Weischedel, Ralph and
Peng, Nanyun",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.719",
doi = "10.18653/v1/2023.emnlp-main.719",
pages = "11753--11770",
}
ALCAP: Alignment-Augmented Music Captioner.
He, Z.; Hao, W.; Lu, W. T.; Chen, C.; Lerman, K.; and Song, X.
In Bouamor, H.; Pino, J.; and Bali, K., editor(s),
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023, pages 16501–16512, 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/emnlp/HeHLCLS23,
author = {Zihao He and
Weituo Hao and
Wei Tsung Lu and
Changyou Chen and
Kristina Lerman and
Xuchen Song},
editor = {Houda Bouamor and
Juan Pino and
Kalika Bali},
title = {{ALCAP:} Alignment-Augmented Music Captioner},
booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural
Language Processing, {EMNLP} 2023, Singapore, December 6-10, 2023},
pages = {16501--16512},
publisher = {Association for Computational Linguistics},
year = {2023},
url = {https://doi.org/10.18653/v1/2023.emnlp-main.1028},
doi = {10.18653/V1/2023.EMNLP-MAIN.1028},
timestamp = {Fri, 12 Apr 2024 01:00:00 +0200},
biburl = {https://dblp.org/rec/conf/emnlp/HeHLCLS23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Active THz Optoelectronics Using Multilayer Graphene: tunable filters, phase modulators, and resonators.
Sachin Sharma, Z. C.; and Chatzakis, I.
In
APS March Meeting Abstracts, volume 2023, of
APS Meeting Abstracts, 2023.
Paper
link
bibtex
@inproceedings{THZ_Device_2023_March_Meeting,
author = {Sachin Sharma, Zhi Cai, Haley A Weinstein, Indu Amma, Stephen B Cronin, and Ioannis Chatzakis},
booktitle = {APS March Meeting Abstracts},
year = 2023,
series = {APS Meeting Abstracts},
volume = {2023},
title = {Active THz Optoelectronics Using Multilayer Graphene: tunable filters, phase modulators, and resonators},
year = {2023},
url = {https://meetings.aps.org/Meeting/MAR23/Session/M21.11},
}
Adapting to the Low-Resource Double-Bind: Investigating Low-Compute Methods on Low-Resource African Languages.
Leong, C.; Shandilya, H.; Dossou, B. F. P.; Tonja, A. L.; Mathew, J.; Omotayo, A.; Yousuf, O.; Akinjobi, Z.; Emezue, C. C.; Muhammad, S.; Kolawole, S.; Choi, Y.; and Adewumi, T.
2023.
link
bibtex
@misc{leong2023adapting,
title={Adapting to the Low-Resource Double-Bind: Investigating Low-Compute Methods on Low-Resource African Languages},
author={Colin Leong and Herumb Shandilya and Bonaventure F. P. Dossou and Atnafu Lambebo Tonja and Joel Mathew and Abdul-Hakeem Omotayo and Oreen Yousuf and Zainab Akinjobi and Chris Chinenye Emezue and Shamsudeen Muhammad and Steven Kolawole and Younwoo Choi and Tosin Adewumi},
year={2023},
eprint={2303.16985},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Affective Polarization in Social Networks.
Feldman, D.; Rao, A.; He, Z.; and Lerman, K.
CoRR, abs/2310.18553. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2310-18553,
author = {Dan Feldman and
Ashwin Rao and
Zihao He and
Kristina Lerman},
title = {Affective Polarization in Social Networks},
journal = {CoRR},
volume = {abs/2310.18553},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2310.18553},
doi = {10.48550/ARXIV.2310.18553},
eprinttype = {arXiv},
eprint = {2310.18553},
timestamp = {Thu, 02 Nov 2023 00:00:00 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2310-18553.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Agile Systems Engineering – Eight Core Aspects.
Dove, R.; Lunney, K.; Orosz, M.; and Yokell, M.
INCOSE International Symposium, 33(1): 823-837. 2023.
Paper
doi
link
bibtex
abstract
@article{https://doi.org/10.1002/iis2.13055,
author = {Dove, Rick and Lunney, Kerry and Orosz, Michael and Yokell, Mike},
title = {Agile Systems Engineering – Eight Core Aspects},
journal = {INCOSE International Symposium},
volume = {33},
number = {1},
pages = {823-837},
doi = {https://doi.org/10.1002/iis2.13055},
url = {https://incose.onlinelibrary.wiley.com/doi/abs/10.1002/iis2.13055},
eprint = {https://incose.onlinelibrary.wiley.com/doi/pdf/10.1002/iis2.13055},
abstract = {Abstract Agile engineering, of any kind, employs strategies for designing, building, sustaining, and evolving purpose-fulfilling creations when knowledge is uncertain and operational environments are dynamic. Strategies address what needs to be accomplished and why, without constraints or directions on how. How those strategies manifest as operational methods depends upon the engineering context. For instance, though single-domain software engineering is different than multi-domain systems engineering, both share the same goals and strategies. This article describes eight agility-supporting strategic aspects with application discussions and examples relevant to systems engineering and exposes common myths and misunderstandings. Each of the eight aspects can individually improve capability to deal with uncertain knowledge and dynamic environments.},
year = {2023}
}
Abstract Agile engineering, of any kind, employs strategies for designing, building, sustaining, and evolving purpose-fulfilling creations when knowledge is uncertain and operational environments are dynamic. Strategies address what needs to be accomplished and why, without constraints or directions on how. How those strategies manifest as operational methods depends upon the engineering context. For instance, though single-domain software engineering is different than multi-domain systems engineering, both share the same goals and strategies. This article describes eight agility-supporting strategic aspects with application discussions and examples relevant to systems engineering and exposes common myths and misunderstandings. Each of the eight aspects can individually improve capability to deal with uncertain knowledge and dynamic environments.
An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks.
Shen, K.; and Kejriwal, M.
Expert Systems,e13243. 2023.
link
bibtex
@article{shen2023experimental,
title={An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks},
author={Shen, Ke and Kejriwal, Mayank},
journal={Expert Systems},
pages={e13243},
year={2023},
publisher={Wiley Online Library}
}
Analyzing Norm Violations in Live-Stream Chat.
Moon, J.; Lee, D.; Cho, H.; Jin, W.; Park, C.; Kim, M.; May, J.; Pujara, J.; and Park, S.
In Bouamor, H.; Pino, J.; and Bali, K., editor(s),
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 852–868, Singapore, December 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
@inproceedings{moon-etal-2023-analyzing,
title = "Analyzing Norm Violations in Live-Stream Chat",
author = "Moon, Jihyung and
Lee, Dong-Ho and
Cho, Hyundong and
Jin, Woojeong and
Park, Chan and
Kim, Minwoo and
May, Jonathan and
Pujara, Jay and
Park, Sungjoon",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.55",
doi = "10.18653/v1/2023.emnlp-main.55",
pages = "852--868",
abstract = "Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and norm violations have been primarily concerned with conversations from online forums and social media, such as Reddit and Twitter. These approaches are less effective when applied to conversations on live-streaming platforms, such as Twitch and YouTube Live, as each comment is only visible for a limited time and lacks a thread structure that establishes its relationship with other comments. In this work, we share the first NLP study dedicated to detecting norm violations in conversations on live-streaming platforms. We define norm violation categories in live-stream chats and annotate 4,583 moderated comments from Twitch. We articulate several facets of live-stream data that differ from other forums, and demonstrate that existing models perform poorly in this setting. By conducting a user study, we identify the informational context humans use in live-stream moderation, and train models leveraging context to identify norm violations. Our results show that appropriate contextual information can boost moderation performance by 35{\%}.",
}
Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and norm violations have been primarily concerned with conversations from online forums and social media, such as Reddit and Twitter. These approaches are less effective when applied to conversations on live-streaming platforms, such as Twitch and YouTube Live, as each comment is only visible for a limited time and lacks a thread structure that establishes its relationship with other comments. In this work, we share the first NLP study dedicated to detecting norm violations in conversations on live-streaming platforms. We define norm violation categories in live-stream chats and annotate 4,583 moderated comments from Twitch. We articulate several facets of live-stream data that differ from other forums, and demonstrate that existing models perform poorly in this setting. By conducting a user study, we identify the informational context humans use in live-stream moderation, and train models leveraging context to identify norm violations. Our results show that appropriate contextual information can boost moderation performance by 35%.
Anger Breeds Controversy: Analyzing Controversy and Emotions on Reddit.
Chen, K.; He, Z.; Chang, R.; May, J.; and Lerman, K.
In Thomson, R.; Al-khateeb, S.; Burger, A.; Park, P. S.; and Pyke, A. A., editor(s),
Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Pittsburgh, PA, USA, September 20-22, 2023, Proceedings, volume 14161, of
Lecture Notes in Computer Science, pages 44–53, 2023. Springer
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/sbp/ChenHCML23,
author = {Kai Chen and
Zihao He and
Rong{-}Ching Chang and
Jonathan May and
Kristina Lerman},
editor = {Robert Thomson and
Samer Al{-}khateeb and
Annetta Burger and
Patrick S. Park and
Aryn A. Pyke},
title = {Anger Breeds Controversy: Analyzing Controversy and Emotions on Reddit},
booktitle = {Social, Cultural, and Behavioral Modeling - 16th International Conference,
SBP-BRiMS 2023, Pittsburgh, PA, USA, September 20-22, 2023, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {14161},
pages = {44--53},
publisher = {Springer},
year = {2023},
url = {https://doi.org/10.1007/978-3-031-43129-6\_5},
doi = {10.1007/978-3-031-43129-6\_5},
timestamp = {Wed, 20 Sep 2023 15:51:04 +0200},
biburl = {https://dblp.org/rec/conf/sbp/ChenHCML23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Artificial Intelligence for Industries of the Future - Beyond Facebook, Amazon, Microsoft and Google.
Kejriwal, M.
Springer, 2023.
Paper
doi
link
bibtex
1 download
@book{DBLP:books/sp/Kejriwal23,
author = {Mayank Kejriwal},
title = {Artificial Intelligence for Industries of the Future - Beyond Facebook,
Amazon, Microsoft and Google},
publisher = {Springer},
year = {2023},
url = {https://doi.org/10.1007/978-3-031-19039-1},
doi = {10.1007/978-3-031-19039-1},
isbn = {978-3-031-19038-4},
timestamp = {Thu, 22 Dec 2022 00:00:00 +0100},
biburl = {https://dblp.org/rec/books/sp/Kejriwal23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Auditing Elon Musk's Impact on Hate Speech and Bots.
Hickey, D.; Schmitz, M.; Fessler, D.; Smaldino, P. E.; Muric, G.; and Burghardt, K.
Proceedings of the International AAAI Conference on Web and Social Media, 17(1): 1133-1137. Jun. 2023.
Paper
doi
link
bibtex
@article{Hickey2023_musk,
abstractnote = {On October 27th, 2022, Elon Musk purchased Twitter, becoming its new CEO and firing many top executives in the process. Musk listed fewer restrictions on content moderation and removal of spam bots among his goals for the platform. Given findings of prior research on moderation and hate speech in online communities, the promise of less strict content moderation poses the concern that hate will rise on Twitter. We examine the levels of hate speech and prevalence of bots before and after Musk's acquisition of the platform. We find that hate speech rose dramatically upon Musk purchasing Twitter and the prevalence of most types of bots increased, while the prevalence of astroturf bots decreased.},
author = {Hickey, Daniel and Schmitz, Matheus and Fessler, Daniel and Smaldino, Paul E. and Muric, Goran and Burghardt, Keith},
doi = {10.1609/icwsm.v17i1.22222},
journal = {Proceedings of the International AAAI Conference on Web and Social Media},
month = {Jun.},
number = {1},
pages = {1133-1137},
title = {Auditing Elon Musk's Impact on Hate Speech and Bots},
url = {https://ojs.aaai.org/index.php/ICWSM/article/view/22222},
volume = {17},
year = {2023},
bdsk-url-1 = {https://ojs.aaai.org/index.php/ICWSM/article/view/22222},
bdsk-url-2 = {https://doi.org/10.1609/icwsm.v17i1.22222}}
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction.
Lee, D.; Selvam, R. K.; Sarwar, S. M.; Lin, B. Y.; Morstatter, F.; Pujara, J.; Boschee, E.; Allan, J.; and Ren, X.
In
European Chapter of the Association for Computational Linguistics, 2023.
link
bibtex
@inproceedings{lee:eacl23,
Author = "Lee, Dong-Ho and Selvam, Ravi Kiran and Sarwar, Sheikh Muhammad and Lin, Bill Yuchen and Morstatter, Fred and Pujara, Jay and Boschee, Elizabeth and Allan, James and Ren, Xiang",
acceptrate = "25\%",
bib_url = "/pubs/bib/lee-eacl23.bib",
booktitle = "European Chapter of the Association for Computational Linguistics",
doi_url = "http://dx.doi.org/10.18653/v1/2023.eacl-main.219",
pdf_url = "/pubs/2023/lee-eacl23/lee-eacl23.pdf",
sec = "conf",
title = "{A}uto{T}rigg{ER}: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction",
year = "2023"
}
Automated Summarization of Stack Overflow Posts.
Kou, B.; Chen, M.; and Zhang, T.
2023.
cite arxiv:2305.16680Comment: ICSE 2023
Paper
link
bibtex
abstract
@misc{kou2023automated,
abstract = {Software developers often resort to Stack Overflow (SO) to fill their
programming needs. Given the abundance of relevant posts, navigating them and
comparing different solutions is tedious and time-consuming. Recent work has
proposed to automatically summarize SO posts to concise text to facilitate the
navigation of SO posts. However, these techniques rely only on information
retrieval methods or heuristics for text summarization, which is insufficient
to handle the ambiguity and sophistication of natural language. This paper
presents a deep learning based framework called ASSORT for SO post
summarization. ASSORT includes two complementary learning methods, ASSORT_S and
ASSORT_{IS}, to address the lack of labeled training data for SO post
summarization. ASSORT_S is designed to directly train a novel ensemble learning
model with BERT embeddings and domainspecific features to account for the
unique characteristics of SO posts. By contrast, ASSORT_{IS} is designed to
reuse pre-trained models while addressing the domain shift challenge when no
training data is present (i.e., zero-shot learning). Both ASSORT_S and
ASSORT_{IS} outperform six existing techniques by at least 13% and 7%
respectively in terms of the F1 score. Furthermore, a human study shows that
participants significantly preferred summaries generated by ASSORT_S and
ASSORT_{IS} over the best baseline, while the preference difference between
ASSORT_S and ASSORT_{IS} was small.},
added-at = {2023-07-11T04:02:52.000+0200},
author = {Kou, Bonan and Chen, Muhao and Zhang, Tianyi},
biburl = {https://www.bibsonomy.org/bibtex/2169cbd6c1b27b97b7c3721b785d97420/woobanseok},
description = {Automated Summarization of Stack Overflow Posts},
interhash = {e1fe7ec4b2a5869e29d4bf9ee58934fb},
intrahash = {169cbd6c1b27b97b7c3721b785d97420},
keywords = {javascript},
note = {cite arxiv:2305.16680Comment: ICSE 2023},
timestamp = {2023-07-11T04:02:52.000+0200},
title = {Automated Summarization of Stack Overflow Posts},
url = {http://arxiv.org/abs/2305.16680},
year = 2023
}
Software developers often resort to Stack Overflow (SO) to fill their programming needs. Given the abundance of relevant posts, navigating them and comparing different solutions is tedious and time-consuming. Recent work has proposed to automatically summarize SO posts to concise text to facilitate the navigation of SO posts. However, these techniques rely only on information retrieval methods or heuristics for text summarization, which is insufficient to handle the ambiguity and sophistication of natural language. This paper presents a deep learning based framework called ASSORT for SO post summarization. ASSORT includes two complementary learning methods, ASSORT_S and ASSORT_IS, to address the lack of labeled training data for SO post summarization. ASSORT_S is designed to directly train a novel ensemble learning model with BERT embeddings and domainspecific features to account for the unique characteristics of SO posts. By contrast, ASSORT_IS is designed to reuse pre-trained models while addressing the domain shift challenge when no training data is present (i.e., zero-shot learning). Both ASSORT_S and ASSORT_IS outperform six existing techniques by at least 13% and 7% respectively in terms of the F1 score. Furthermore, a human study shows that participants significantly preferred summaries generated by ASSORT_S and ASSORT_IS over the best baseline, while the preference difference between ASSORT_S and ASSORT_IS was small.
Automatic Semantic Typing of Pet E-commerce Products Using Crowdsourced Reviews: An Experimental Study.
Liu, X.; Sun, T.; Fu, D.; Li, Z.; Qian, S.; Meng, R.; and Kejriwal, M.
In
Iberoamerican Knowledge Graphs and Semantic Web Conference, pages 151–167, 2023. Springer
link
bibtex
@inproceedings{liu2023automatic,
title={Automatic Semantic Typing of Pet E-commerce Products Using Crowdsourced Reviews: An Experimental Study},
author={Liu, Xinyu and Sun, Tiancheng and Fu, Diantian and Li, Zijue and Qian, Sheng and Meng, Ruyue and Kejriwal, Mayank},
booktitle={Iberoamerican Knowledge Graphs and Semantic Web Conference},
pages={151--167},
year={2023},
organization={Springer}
}
Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification.
Chiu, M.; Chen, P.; and Ma, X.
In
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pages 4956-4966, October 2023.
link
bibtex
@InProceedings{Chiu_2023_ICCV,
author = {Chiu, Ming-Chang and Chen, Pin-Yu and Ma, Xuezhe},
title = {Better May Not Be Fairer: A Study on Subgroup Discrepancy in Image Classification},
booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
month = {October},
year = {2023},
pages = {4956-4966}
}
Bitstream Assurance Checking Engine for Undocumented Functionality (BRACE).
A. Schmidt, J. W.; and B. Reynwar, T. S.
March 2023.
link
bibtex
@conference {Schmidt2023,
title = {Bitstream Assurance Checking Engine for Undocumented Functionality (BRACE)},
organization = {Government Microcircuit Applications and Critical Technology Conference (GOMACTech)},
year = {2023},
month = {March},
author = {A. Schmidt, J. Wilford, B. Reynwar, T. Sung, M. French, },
ISIArea = {CAS, MES}
}
Blend and Match: Distilling Semantic Search Models with Different Inductive Biases and Model Architectures.
Bonab, H.; Joshi, A.; Bhatia, R.; Gandhi, A.; Huddar, V.; Naik, J.; Al-Darabsah, M.; Teo, C. H.; May, J.; Agarwal, T.; and Petricek, V.
In
Companion Proceedings of the ACM Web Conference 2023, of
WWW '23 Companion, pages 869–877, New York, NY, USA, 2023. Association for Computing Machinery
Paper
doi
link
bibtex
abstract
@inproceedings{10.1145/3543873.3587629,
author = {Bonab, Hamed and Joshi, Ashutosh and Bhatia, Ravi and Gandhi, Ankit and Huddar, Vijay and Naik, Juhi and Al-Darabsah, Mutasem and Teo, Choon Hui and May, Jonathan and Agarwal, Tarun and Petricek, Vaclav},
title = {Blend and Match: Distilling Semantic Search Models with Different Inductive Biases and Model Architectures},
year = {2023},
isbn = {9781450394192},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3543873.3587629},
doi = {10.1145/3543873.3587629},
abstract = {Commercial search engines use different semantic models to augment lexical matches. These models provide candidate items for a user’s query from a target space of millions to billions of items. Models with different inductive biases provide relatively different predictions, making it desirable to launch multiple semantic models in production. However, latency and resource constraints make simultaneously deploying multiple models impractical. In this paper, we introduce a distillation approach, called Blend and Match (BM), to unify two different semantic search models into a single model. We use a Bi-encoder semantic matching model as our primary model and propose a novel loss function to incorporate eXtreme Multi-label Classification (XMC) predictions as the secondary model. Our experiments conducted on two large-scale datasets, collected from a popular e-commerce store, show that our proposed approach significantly improves the recall of the primary Bi-encoder model by 11\% to 17\% with a minimal loss in precision. We show that traditional knowledge distillation approaches result in a sub-optimal performance for our problem setting, and our BM approach yields comparable rankings with strong Rank Fusion (RF) methods used only if one could deploy multiple models.},
booktitle = {Companion Proceedings of the ACM Web Conference 2023},
pages = {869–877},
numpages = {9},
keywords = {Semantic Search, Ranking Distillation, Product Search, Model Blending},
location = {Austin, TX, USA},
series = {WWW '23 Companion}
}
Commercial search engines use different semantic models to augment lexical matches. These models provide candidate items for a user’s query from a target space of millions to billions of items. Models with different inductive biases provide relatively different predictions, making it desirable to launch multiple semantic models in production. However, latency and resource constraints make simultaneously deploying multiple models impractical. In this paper, we introduce a distillation approach, called Blend and Match (BM), to unify two different semantic search models into a single model. We use a Bi-encoder semantic matching model as our primary model and propose a novel loss function to incorporate eXtreme Multi-label Classification (XMC) predictions as the secondary model. Our experiments conducted on two large-scale datasets, collected from a popular e-commerce store, show that our proposed approach significantly improves the recall of the primary Bi-encoder model by 11% to 17% with a minimal loss in precision. We show that traditional knowledge distillation approaches result in a sub-optimal performance for our problem setting, and our BM approach yields comparable rankings with strong Rank Fusion (RF) methods used only if one could deploy multiple models.
Bridging the Gap between Native Text and Translated Text through Adversarial Learning: A Case Study on Cross-Lingual Event Extraction.
Yu, P.; May, J.; and Ji, H.
In
Findings of the Association for Computational Linguistics: EACL 2023, pages 754–769, Dubrovnik, Croatia, May 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
@inproceedings{yu-etal-2023-bridging,
title = "Bridging the Gap between Native Text and Translated Text through Adversarial Learning: A Case Study on Cross-Lingual Event Extraction",
author = "Yu, Pengfei and
May, Jonathan and
Ji, Heng",
booktitle = "Findings of the Association for Computational Linguistics: EACL 2023",
month = may,
year = "2023",
address = "Dubrovnik, Croatia",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.findings-eacl.57",
doi = "10.18653/v1/2023.findings-eacl.57",
pages = "754--769",
abstract = "Recent research in cross-lingual learning has found that combining large-scale pretrained multilingual language models with machine translation can yield good performance. We explore this idea for cross-lingual event extraction with a new model architecture that jointly encodes a source language input sentence with its translation to the target language during training, and takes a target language sentence with its translation back to the source language as input during evaluation. However, we observe significant representational gap between the native source language texts during training and the texts translated into source language during evaluation, as well as the texts translated into target language during training and the native target language texts during evaluation. This representational gap undermines the effectiveness of cross-lingual transfer learning for event extraction with machine-translated data. In order to mitigate this problem, we propose an adversarial training framework that encourages the language model to produce more similar representations for the translated text and the native text. To be specific, we train the language model such that its hidden representations are able to fool a jointly trained discriminator that distinguishes translated texts{'} representations from native texts{'} representations. We conduct experiments on cross-lingual for event extraction across three languages. Results demonstrate that our proposed adversarial training can effectively incorporate machine translation to improve event extraction, while simply adding machine-translated data yields unstable performance due to the representational gap.",
}
Recent research in cross-lingual learning has found that combining large-scale pretrained multilingual language models with machine translation can yield good performance. We explore this idea for cross-lingual event extraction with a new model architecture that jointly encodes a source language input sentence with its translation to the target language during training, and takes a target language sentence with its translation back to the source language as input during evaluation. However, we observe significant representational gap between the native source language texts during training and the texts translated into source language during evaluation, as well as the texts translated into target language during training and the native target language texts during evaluation. This representational gap undermines the effectiveness of cross-lingual transfer learning for event extraction with machine-translated data. In order to mitigate this problem, we propose an adversarial training framework that encourages the language model to produce more similar representations for the translated text and the native text. To be specific, we train the language model such that its hidden representations are able to fool a jointly trained discriminator that distinguishes translated texts' representations from native texts' representations. We conduct experiments on cross-lingual for event extraction across three languages. Results demonstrate that our proposed adversarial training can effectively incorporate machine translation to improve event extraction, while simply adding machine-translated data yields unstable performance due to the representational gap.
Broadening Student Engagement To Build the Next Generation of Cyberinfrastructure Professionals.
Murillo, A.; Brower, D.; Hossain, S.; Kee, K.; Mandal, A.; Nabrzyski, J.; Scott, E.; Virdone, N.; Ewing, R.; and Deelman, E.
In
Practice and Experience in Advanced Research Computing, of
PEARC '23, pages 470–473, New York, NY, USA, 2023. Association for Computing Machinery
Funding Acknowledgments: NSF 2127548
Paper
doi
link
bibtex
@InProceedings{ murillo-pearc-2023,
Author = {Murillo, Angela and Brower, Don and Hossain, Sarowar and
Kee, Kerk and Mandal, Anirban and Nabrzyski, Jarek and
Scott, Erik and Virdone, Nicole and Ewing, Rodney and
Deelman, Ewa},
Title = {Broadening Student Engagement To Build the Next Generation
of Cyberinfrastructure Professionals},
Year = {2023},
ISBN = {9781450399852},
Publisher = {Association for Computing Machinery},
Address = {New York, NY, USA},
URL = {https://doi.org/10.1145/3569951.3597567},
DOI = {10.1145/3569951.3597567},
BookTitle = {Practice and Experience in Advanced Research Computing},
Pages = {470–473},
numpages = {4},
Keywords = {workforce development, cyberinfrastructure, Student
fellowships, Major Facilities},
Location = {Portland, OR, USA},
Series = {PEARC '23},
Note = {Funding Acknowledgments: NSF 2127548}
}
.
Ilievski, F.; Ma, K.; Oltramari, A.; Wang, P.; and Pujara, J.
Building Robust and Explainable AI with Commonsense Knowledge Graphs and Neural Models, pages 178 - 209. IOS Press, Nieuwe Hemweg 6B, 1013 BG Amsterdam, NL, 2023.
link
bibtex
@inbook{ilievski:cnsai23,
Author = "Ilievski, Filip and Ma, Kaixin and Oltramari, Alessandro and Wang, Peifeng and Pujara, Jay",
address = "Nieuwe Hemweg 6B, 1013 BG Amsterdam, NL",
booktitle = "Compendium of Neurosymbolic Artificial Intelligence",
isbn = "978-1-64368-406-2",
pages = "178 - 209",
publisher = "IOS Press",
title = "Building Robust and Explainable AI with Commonsense Knowledge Graphs and Neural Models",
year = "2023"
}
Building Spatio-Temporal Knowledge Graphs from Vectorized Topographic Historical Maps.
Shbita, B.; Knoblock, C. A; Duan, W.; Chiang, Y.; Uhl, J. H; and Leyk, S.
Semantic Web, 14(3): 527–549. 2023.
Link
Paper
Slides
link
bibtex
20 downloads
@article{shbita2023building,
title={Building Spatio-Temporal Knowledge Graphs from Vectorized Topographic Historical Maps},
author={Shbita, Basel and Knoblock, Craig A and Duan, Weiwei and Chiang, Yao-Yi and Uhl, Johannes H and Leyk, Stefan},
journal={Semantic Web},
volume={14},
number={3},
pages={527--549},
year={2023},
publisher={IOS Press},
urlLink={https://content.iospress.com/articles/semantic-web/sw222918},
urlPaper={http://usc-isi-i2.github.io/papers/shbita23-swj.pdf},
urlSlides={http://usc-isi-i2.github.io/slides/shbita23-swj-slides.pdf}
}
Building Upon the EarthCube Community: a geoscience and cyberinfrastructure workshop - Report.
Khider, D.; Mike Daniels; and Jarboe, N.
Technical Report 2023.
Paper
link
bibtex
abstract
@techreport{khider_building_2023,
title = {Building {Upon} the {EarthCube} {Community}: a geoscience and cyberinfrastructure workshop - {Report}},
copyright = {Creative Commons Attribution 4.0 International},
shorttitle = {Building {Upon} the {EarthCube} {Community}},
url = {https://figshare.com/articles/conference_contribution/Building_Upon_the_EarthCube_Community_a_geoscience_and_cyberinfrastructure_workshop_-_Report/23949168/2},
abstract = {This report summarizes the discussion at the "Building Upon the EarthCube Community: A geoscience and cyberinfrastructure workshop" which was held at the University of Southern California Information Sciences Institute, June 27-28th 2023.},
urldate = {2024-01-25},
author = {Khider, Deborah and {Mike Daniels} and Jarboe, Nick},
year = {2023},
keywords = {Earth and space science informatics},
pages = {9095054 Bytes},
}
This report summarizes the discussion at the "Building Upon the EarthCube Community: A geoscience and cyberinfrastructure workshop" which was held at the University of Southern California Information Sciences Institute, June 27-28th 2023.
CPL-NoViD: Context-Aware Prompt-based Learning for Norm Violation Detection in Online Communities.
He, Z.; May, J.; and Lerman, K.
CoRR, abs/2305.09846. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2305-09846,
author = {Zihao He and
Jonathan May and
Kristina Lerman},
title = {CPL-NoViD: Context-Aware Prompt-based Learning for Norm Violation
Detection in Online Communities},
journal = {CoRR},
volume = {abs/2305.09846},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2305.09846},
doi = {10.48550/ARXIV.2305.09846},
eprinttype = {arXiv},
eprint = {2305.09846},
timestamp = {Wed, 24 May 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2305-09846.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Can Language Models Be Used in Multistep Commonsense Planning Domains?.
Tang, Z.; and Kejriwal, M.
In
International Conference on Artificial General Intelligence, pages 276–285, 2023. Springer
link
bibtex
@inproceedings{tang2023can1,
title={Can Language Models Be Used in Multistep Commonsense Planning Domains?},
author={Tang, Zhisheng and Kejriwal, Mayank},
booktitle={International Conference on Artificial General Intelligence},
pages={276--285},
year={2023},
organization={Springer}
}
Can language representation models think in bets?.
Tang, Z.; and Kejriwal, M.
Royal Society Open Science, 10(3): 221585. 2023.
link
bibtex
@article{tang2023can,
title={Can language representation models think in bets?},
author={Tang, Zhisheng and Kejriwal, Mayank},
journal={Royal Society Open Science},
volume={10},
number={3},
pages={221585},
year={2023},
publisher={The Royal Society}
}
Can the United States Maintain Its Leadership in High-Performance Computing?-A report from the ASCAC Subcommittee on American Competitiveness and Innovation to the ASCR Office.
Dongarra, J.; Deelman, E.; Hey, T.; Matsuoka, S.; Sarakar, V.; Bell, G.; Foster, I.; Keyes, D.; and Kranzlmueller, D. e.
OSTI. 2023.
doi
link
bibtex
@Article{ dongarra-osti-2023,
Author = {Dongarra, Jack and Deelman, Ewa and Hey, Tony and
Matsuoka, Satoshi and Sarakar, Vivek and Bell, Greg and
Foster, Ian and Keyes, David, and Kranzlmueller, Dieter
et-al},
Journal = {OSTI},
Title = {Can the United States Maintain Its Leadership in
High-Performance Computing?-A report from the ASCAC
Subcommittee on American Competitiveness and Innovation to
the ASCR Office},
Year = {2023},
Volume = {},
Number = {},
Pages = {},
DOI = {10.2172/1989107}
}
Capturing Perspectives of Crowdsourced Annotators in Subjective Learning Tasks.
Mokhberian, N.; Marmarelis, M. G.; Hopp, F. R.; Basile, V.; Morstatter, F.; and Lerman, K.
CoRR, abs/2311.09743. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2311-09743,
author = {Negar Mokhberian and
Myrl G. Marmarelis and
Frederic R. Hopp and
Valerio Basile and
Fred Morstatter and
Kristina Lerman},
title = {Capturing Perspectives of Crowdsourced Annotators in Subjective Learning
Tasks},
journal = {CoRR},
volume = {abs/2311.09743},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2311.09743},
doi = {10.48550/ARXIV.2311.09743},
eprinttype = {arXiv},
eprint = {2311.09743},
timestamp = {Tue, 21 Nov 2023 00:00:00 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2311-09743.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Challenges in Context-Aware Neural Machine Translation.
Jin, L.; He, J.; May, J.; and Ma, X.
In Bouamor, H.; Pino, J.; and Bali, K., editor(s),
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 15246–15263, Singapore, December 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
2 downloads
@inproceedings{jin-etal-2023-challenges,
title = "Challenges in Context-Aware Neural Machine Translation",
author = "Jin, Linghao and
He, Jacqueline and
May, Jonathan and
Ma, Xuezhe",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.943",
doi = "10.18653/v1/2023.emnlp-main.943",
pages = "15246--15263",
abstract = "Context-aware neural machine translation, a paradigm that involves leveraging information beyond sentence-level context to resolve inter-sentential discourse dependencies and improve document-level translation quality, has given rise to a number of recent techniques. However, despite well-reasoned intuitions, most context-aware translation models show only modest improvements over sentence-level systems. In this work, we investigate and present several core challenges that impede progress within the field, relating to discourse phenomena, context usage, model architectures, and document-level evaluation. To address these problems, we propose a more realistic setting for document-level translation, called paragraph-to-paragraph (PARA2PARA) translation, and collect a new dataset of Chinese-English novels to promote future research.",
}
Context-aware neural machine translation, a paradigm that involves leveraging information beyond sentence-level context to resolve inter-sentential discourse dependencies and improve document-level translation quality, has given rise to a number of recent techniques. However, despite well-reasoned intuitions, most context-aware translation models show only modest improvements over sentence-level systems. In this work, we investigate and present several core challenges that impede progress within the field, relating to discourse phenomena, context usage, model architectures, and document-level evaluation. To address these problems, we propose a more realistic setting for document-level translation, called paragraph-to-paragraph (PARA2PARA) translation, and collect a new dataset of Chinese-English novels to promote future research.
Changes in Research Collaborations During the Pandemic.
Wang, Z.; Ahrabian, K.; Rusti, C.; Pujara, J.; and Lerman, K.
In
International Society of Scientometrics and Informetrics Conference, 2023.
link
bibtex
@inproceedings{wang:issi23,
Author = "Wang, Ziao and Ahrabian, Kian and Rusti, Casandra and Pujara, Jay and Lerman, Kristina",
bib_url = "/pubs/bib/wang-issi23.bib",
booktitle = "International Society of Scientometrics and Informetrics Conference",
pdf_url = "/pubs/2023/wang-issi23/wang-issi23.pdf",
sec = "ws",
title = "Changes in Research Collaborations During the Pandemic",
year = "2023"
}
Classifying Seismograms Using the FastMap Algorithm and Support-Vector Machines.
White, M.; Sharma, K.; Li, A.; Thittamaranahalli, S.; and Nakata, N.
Nature Communications Engineering (NATURE-COMMSENG-2023). 2023.
link
bibtex
@article{tksk10,
author={Malcolm White and Kushal Sharma and Ang Li and Satish Thittamaranahalli and Nori Nakata},
title={Classifying Seismograms Using the FastMap Algorithm and Support-Vector Machines},
journal={Nature Communications Engineering (NATURE-COMMSENG-2023)},
year={2023}
}
Clique Densification in Networks.
Pi, H.; Burghardt, K.; Percus, A. G.; and Lerman, K.
CoRR, abs/2304.03479. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2304-03479,
author = {Haochen Pi and
Keith Burghardt and
Allon G. Percus and
Kristina Lerman},
title = {Clique Densification in Networks},
journal = {CoRR},
volume = {abs/2304.03479},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2304.03479},
doi = {10.48550/ARXIV.2304.03479},
eprinttype = {arXiv},
eprint = {2304.03479},
timestamp = {Tue, 18 Apr 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2304-03479.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Comparison of Knowledge Graph Representations for Consumer Scenarios.
Iglesias-Molina, A.; Ahrabian, K.; Ilievski, F.; Pujara, J.; and Corcho, O.
In
International Semantic Web Conference, 2023.
link
bibtex
@inproceedings{molina:iswc23,
Author = "Iglesias-Molina, Ana and Ahrabian, Kian and Ilievski, Filip and Pujara, Jay and Corcho, Oscar",
acceptrate = "16\%",
bib_url = "/pubs/bib/molina-iswc23.bib",
booktitle = "International Semantic Web Conference",
pdf_url = "/pubs/2023/molina-iswc23/molina-iswc23.pdf",
sec = "conf",
title = "Comparison of Knowledge Graph Representations for Consumer Scenarios",
year = "2023"
}
Context-Rich Evaluation of Machine Common Sense.
Kejriwal, M.; Santos, H.; Shen, K.; Mulvehill, A. M; and McGuinness, D. L
In
International Conference on Artificial General Intelligence, pages 167–176, 2023. Springer
link
bibtex
@inproceedings{kejriwal2023context,
title={Context-Rich Evaluation of Machine Common Sense},
author={Kejriwal, Mayank and Santos, Henrique and Shen, Ke and Mulvehill, Alice M and McGuinness, Deborah L},
booktitle={International Conference on Artificial General Intelligence},
pages={167--176},
year={2023},
organization={Springer}
}
Contextualizing Argument Quality Assessment with Relevant Knowledge.
Deshpande, D.; Sourati, Z.; Ilievski, F.; and Morstatter, F.
arXiv preprint arXiv:2305.12280. 2023.
link
bibtex
@article{deshpande2023contextualizing,
title={Contextualizing Argument Quality Assessment with Relevant Knowledge},
author={Deshpande, Darshan and Sourati, Zhivar and Ilievski, Filip and Morstatter, Fred},
journal={arXiv preprint arXiv:2305.12280},
year={2023}
}
Contextualizing Internet Memes Across Social Media Platforms.
Joshi, S.; Ilievski, F.; and Luceri, L.
arXiv Preprint: https://arxiv.org/abs/2311.11157, 2023.
link
bibtex
@misc{joshi2023contextualizing,
title={Contextualizing Internet Memes Across Social Media Platforms},
author={Joshi, Saurav and Ilievski, Filip and Luceri, Luca},
Eprint = {arXiv:2311.11157},
Howpublished = {arXiv Preprint: https://arxiv.org/abs/2311.11157},
year={2023}
}
Continual Dialogue State Tracking via Example-Guided Question Answering.
Cho, H.; Madotto, A.; Lin, Z.; Chandu, K.; Kottur, S.; Xu, J.; May, J.; and Sankar, C.
In Bouamor, H.; Pino, J.; and Bali, K., editor(s),
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 3873–3886, Singapore, December 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
@inproceedings{cho-etal-2023-continual,
title = "Continual Dialogue State Tracking via Example-Guided Question Answering",
author = "Cho, Hyundong and
Madotto, Andrea and
Lin, Zhaojiang and
Chandu, Khyathi and
Kottur, Satwik and
Xu, Jing and
May, Jonathan and
Sankar, Chinnadhurai",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.235",
doi = "10.18653/v1/2023.emnlp-main.235",
pages = "3873--3886",
abstract = "Dialogue systems are frequently updated to accommodate new services, but naively updating them by continually training with data for new services in diminishing performance on previously learnt services. Motivated by the insight that dialogue state tracking (DST), a crucial component of dialogue systems that estimates the user{'}s goal as a conversation proceeds, is a simple natural language understanding task, we propose reformulating it as a bundle of granular example-guided question answering tasks to minimize the task shift between services and thus benefit continual learning. Our approach alleviates service-specific memorization and teaches a model to contextualize the given question and example to extract the necessary information from the conversation. We find that a model with just 60M parameters can achieve a significant boost by learning to learn from in-context examples retrieved by a retriever trained to identify turns with similar dialogue state changes. Combining our method with dialogue-level memory replay, our approach attains state of the art performance on DST continual learning metrics without relying on any complex regularization or parameter expansion methods.",
}
Dialogue systems are frequently updated to accommodate new services, but naively updating them by continually training with data for new services in diminishing performance on previously learnt services. Motivated by the insight that dialogue state tracking (DST), a crucial component of dialogue systems that estimates the user's goal as a conversation proceeds, is a simple natural language understanding task, we propose reformulating it as a bundle of granular example-guided question answering tasks to minimize the task shift between services and thus benefit continual learning. Our approach alleviates service-specific memorization and teaches a model to contextualize the given question and example to extract the necessary information from the conversation. We find that a model with just 60M parameters can achieve a significant boost by learning to learn from in-context examples retrieved by a retriever trained to identify turns with similar dialogue state changes. Combining our method with dialogue-level memory replay, our approach attains state of the art performance on DST continual learning metrics without relying on any complex regularization or parameter expansion methods.
Cross-lingual Continual Learning.
M'hamdi, M.; Ren, X.; and May, J.
In
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 3908–3943, Toronto, Canada, July 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
@inproceedings{mhamdi-etal-2023-cross,
title = "Cross-lingual Continual Learning",
author = "M{'}hamdi, Meryem and
Ren, Xiang and
May, Jonathan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.217",
doi = "10.18653/v1/2023.acl-long.217",
pages = "3908--3943",
abstract = "The longstanding goal of multi-lingual learning has been to develop a universal cross-lingual model that can withstand the changes in multi-lingual data distributions. There has been a large amount of work to adapt such multi-lingual models to unseen target languages. However, the majority of work in this direction focuses on the standard one-hop transfer learning pipeline from source to target languages, whereas in realistic scenarios, new languages can be incorporated at any time in a sequential manner. In this paper, we present a principled Cross-lingual Continual Learning (CCL) evaluation paradigm, where we analyze different categories of approaches used to continually adapt to emerging data from different languages. We provide insights into what makes multilingual sequential learning particularly challenging. To surmount such challenges, we benchmark a representative set of cross-lingual continual learning algorithms and analyze their knowledge preservation, accumulation, and generalization capabilities compared to baselines on carefully curated datastreams. The implications of this analysis include a recipe for how to measure and balance different cross-lingual continual learning desiderata, which go beyond conventional transfer learning.",
}
The longstanding goal of multi-lingual learning has been to develop a universal cross-lingual model that can withstand the changes in multi-lingual data distributions. There has been a large amount of work to adapt such multi-lingual models to unseen target languages. However, the majority of work in this direction focuses on the standard one-hop transfer learning pipeline from source to target languages, whereas in realistic scenarios, new languages can be incorporated at any time in a sequential manner. In this paper, we present a principled Cross-lingual Continual Learning (CCL) evaluation paradigm, where we analyze different categories of approaches used to continually adapt to emerging data from different languages. We provide insights into what makes multilingual sequential learning particularly challenging. To surmount such challenges, we benchmark a representative set of cross-lingual continual learning algorithms and analyze their knowledge preservation, accumulation, and generalization capabilities compared to baselines on carefully curated datastreams. The implications of this analysis include a recipe for how to measure and balance different cross-lingual continual learning desiderata, which go beyond conventional transfer learning.
Data-Driven Template-Free Invariant Generation.
Xia, Y.; Deshmukh, J. V.; Raghothaman, M.; and Ravi, S.
CoRR, abs/2312.17527. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2312-17527,
author = {Yuan Xia and
Jyotirmoy V. Deshmukh and
Mukund Raghothaman and
Srivatsan Ravi},
title = {Data-Driven Template-Free Invariant Generation},
journal = {CoRR},
volume = {abs/2312.17527},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2312.17527},
doi = {10.48550/ARXIV.2312.17527},
eprinttype = {arXiv},
eprint = {2312.17527},
timestamp = {Fri, 19 Jan 2024 13:27:20 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2312-17527.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Database Evolution, by Scientists, for Scientists: A Case Study.
Schuler, R.; Singla, J.; Vallat, B.; White, K. L.; Berman, H. M.; and Kesselman, C.
In
2023 IEEE 19th International Conference on E-Science (e-Science), pages 1–10, Limassol, Cyprus, October 2023. IEEE
doi
link
bibtex
abstract
@inproceedings{Schuler2023,
abstract = {Database management systems have been used to great advantage for industry usage scenarios. As science becomes increasingly dependent on carefully organized and curated data to inform and drive new discoveries, the need for database management systems has grown significantly. The long standing ``20 questions'' method was advocated in early studies of applying relational databases for science in order to elicit requirements for designing and developing information systems for scientific data. It has been observed, however, that database designs become outdated within months of usage leading to degradation in the quality of the database schema. In addition, there is limited evidence that scientists themselves have the tools and processes necessary to develop and maintain scientific databases without reliance on database administrators. Beyond learning to query databases, scientists need tools to create and evolve databases and guidance on how to apply those tools to develop information systems. In this paper, we present a simplified methodology for database evolution for scientists and a case study of database evolution by a scientist in the context of a research database for cell modeling. We include a detailed analysis of the activities and processes employed by the scientist during the schema evolution. Our results show that a scientist can successfully evolve a complex information system driven by new research requirements.},
address = {{Limassol, Cyprus}},
author = {Schuler, Robert and Singla, Jitin and Vallat, Brinda and White, Kate L. and Berman, Helen M. and Kesselman, Carl},
booktitle = {2023 {{IEEE}} 19th {{International Conference}} on E-{{Science}} (e-{{Science}})},
date-added = {2024-01-22 12:05:54 -0800},
date-modified = {2024-01-22 12:05:54 -0800},
doi = {10.1109/e-Science58273.2023.10254872},
file = {/Users/schuler/Zotero/storage/L493H8AJ/Schuler et al. - 2022 - Relational Database Schema Evolution, by Scientist.pdf;/Users/schuler/Zotero/storage/PD8URSG9/CHiSEL_CaseStudy_2022.pdf},
keywords = {in review},
month = oct,
pages = {1--10},
publisher = {{IEEE}},
title = {Database {{Evolution}}, by {{Scientists}}, for {{Scientists}}: {{A Case Study}}},
year = {2023},
bdsk-url-1 = {https://doi.org/10.1109/e-Science58273.2023.10254872}}
Database management systems have been used to great advantage for industry usage scenarios. As science becomes increasingly dependent on carefully organized and curated data to inform and drive new discoveries, the need for database management systems has grown significantly. The long standing ``20 questions'' method was advocated in early studies of applying relational databases for science in order to elicit requirements for designing and developing information systems for scientific data. It has been observed, however, that database designs become outdated within months of usage leading to degradation in the quality of the database schema. In addition, there is limited evidence that scientists themselves have the tools and processes necessary to develop and maintain scientific databases without reliance on database administrators. Beyond learning to query databases, scientists need tools to create and evolve databases and guidance on how to apply those tools to develop information systems. In this paper, we present a simplified methodology for database evolution for scientists and a case study of database evolution by a scientist in the context of a research database for cell modeling. We include a detailed analysis of the activities and processes employed by the scientist during the schema evolution. Our results show that a scientist can successfully evolve a complex information system driven by new research requirements.
Deep Learning Recommendation Model Training Co-design with the Dynamic Opera Network.
Imes, C.; Rittenbach, A.; Xie, P.; Kang, D. I. D; Walters, J. P.; and Crago, S. P
HPEC. 2023.
link
bibtex
@article{imesHPEC2023extabs,
title={Deep Learning Recommendation Model Training Co-design with the Dynamic Opera Network},
author={Imes, Connor and Rittenbach, Andrew and Xie, Peng and Kang, Dong In D and Walters, John Paul and Crago, Stephen P},
journal={HPEC},
year={2023},
ISIArea = {ML, CAS, NET}
}
Defending Root DNS Servers Against DDoS Using Layered Defenses.
Rizvi, A.; Mirkovic, J.; adn Wes Hardaker, J. H.; and Story, R.
In
Proceedings of the IEEE International Conference on Communications Systems and Netowrks (COMSNETS), pages to appear, Bengaluru, India, January 2023. IEEE
Awarded best paper
Paper
link
bibtex
@inproceedings{Rizvi23a,
author = {Rizvi, {A S M} and Mirkovic, Jelena and adn Wes Hardaker, John Heidemann and Story, Robert},
title = {Defending Root {DNS} Servers Against {DDoS} Using Layered Defenses},
booktitle = {Proceedings of the {IEEE} International Conference on Communications Systems and Netowrks (COMSNETS)},
year = {2023},
sortdate = {2023-01-03},
project = {ant, ddidd, paaddos},
jsubject = {network_security},
note = {Awarded best paper},
pages = {to appear},
month = jan,
address = {Bengaluru, India},
publisher = {IEEE},
location = {johnh: pafile},
keywords = {ddidd, ddos, filtering, frade},
xdoi = {tbd},
blogurl = {https://ant.isi.edu/blog/?p=1948},
url = {https://www.isi.edu/%7ejohnh/PAPERS/Rizvi23a.html},
pdfurl = {https://www.isi.edu/%7ejohnh/PAPERS/Rizvi23a.pdf}
}
Defending Root DNS Servers Against DDoS Using Layered Defenses.
Rizvi, A S M; Mirkovic, J.; Heidemann, J.; Hardaker, W.; and Story, R.
In
IEEE COMSNETS, 2023.
link
bibtex
@inproceedings{zvi87632023,
author={A S M Rizvi and Jelena Mirkovic and John Heidemann and Wesley Hardaker and Robert Story},
title={Defending Root DNS Servers Against DDoS Using Layered Defenses},
booktitle={IEEE COMSNETS},
year={2023}}
Defending Root DNS Servers Against DDoS Using Layered Defenses (Extended).
Rizvi, A.; Mirkovic, J.; Heidemann, J.; Hardaker, W.; and Story, R.
Ad Hoc Networks Journal, 151. December 2023.
Paper
doi
link
bibtex
abstract
@Article{Rizvi23b,
author = "{A S M} Rizvi and Jelena Mirkovic and John
Heidemann and Wes Hardaker and Robert Story",
title = "Defending Root {DNS} Servers Against {DDoS} Using Layered
Defenses (Extended)",
journal = "Ad Hoc Networks Journal",
year = 2023,
volume = 151,
xpages = "no pages",
month = dec,
sortdate = "2023-12-01",
project = "ant, ddidd, paaddos",
jsubject = "network_security",
publisher = "Elsevier Science Publishing Co., Inc.",
jlocation = "johnh: pafile",
keywords = "ddidd, ddos, filtering, frade",
doi = "https://doi.org/10.1016/j.adhoc.2023.103259",
xblogurl = "https://ant.isi.edu/blog/?p=tbd",
url = "https://ant.isi.edu/%7ejohnh/PAPERS/Rizvi23b.html",
pdfurl = "https://ant.isi.edu/%7ejohnh/PAPERS/Rizvi23b.pdf",
abstract = "Distributed Denial-of-Service (DDoS) attacks exhaust resources, leaving a server unavailable to legitimate clients. The Domain Name System (DNS) is a frequent target of DDoS attacks. Since DNS is a critical infrastructure service, protecting it from DoS is imperative. Many prior approaches have focused on specific filters or anti-spoofing techniques to protect generic services. DNS root nameservers are more challenging to protect, since they use fixed IP addresses, serve very diverse clients and requests, receive predominantly UDP traffic that can be spoofed, and must guarantee high quality of service. In this paper we propose a layered DDoS defense for DNS root nameservers. Our defense uses a \emph{library} of defensive filters, which can be optimized for different attack types, with different levels of selectivity. We further propose a method that \emph{automatically and continuously evaluates and selects} the best combination of filters throughout the attack. We show that this layered defense approach provides exceptional protection against all attack types using traces of ten real attacks from a DNS root nameserver. Our automated system can select the best defense within seconds and quickly reduces traffic to the server within a manageable range, while keeping collateral damage lower than 2\%. We show our system can successfully mitigate resource exhaustion using replay of a real-world attack. We can handle millions of filtering rules without noticeable operational overhead."
,}
Distributed Denial-of-Service (DDoS) attacks exhaust resources, leaving a server unavailable to legitimate clients. The Domain Name System (DNS) is a frequent target of DDoS attacks. Since DNS is a critical infrastructure service, protecting it from DoS is imperative. Many prior approaches have focused on specific filters or anti-spoofing techniques to protect generic services. DNS root nameservers are more challenging to protect, since they use fixed IP addresses, serve very diverse clients and requests, receive predominantly UDP traffic that can be spoofed, and must guarantee high quality of service. In this paper we propose a layered DDoS defense for DNS root nameservers. Our defense uses a \emphlibrary of defensive filters, which can be optimized for different attack types, with different levels of selectivity. We further propose a method that \emphautomatically and continuously evaluates and selects the best combination of filters throughout the attack. We show that this layered defense approach provides exceptional protection against all attack types using traces of ten real attacks from a DNS root nameserver. Our automated system can select the best defense within seconds and quickly reduces traffic to the server within a manageable range, while keeping collateral damage lower than 2%. We show our system can successfully mitigate resource exhaustion using replay of a real-world attack. We can handle millions of filtering rules without noticeable operational overhead.
Demonstration of optically-assisted reconfigurable average of two 20-Gbaud 4-phase-encoded data channels using nonlinear wave mixing.
Minoofar, A.; Karapetyan, N.; Almaiman, A.; Zhou, H.; Song, H.; Zou, K.; Ko, W.; Ramakrishnan, M.; Annavaram, M.; Habif, J. L; and others
Optics Letters, 48(17): 4617–4620. 2023.
link
bibtex
@article{minoofar2023demonstration,
title={Demonstration of optically-assisted reconfigurable average of two 20-Gbaud 4-phase-encoded data channels using nonlinear wave mixing},
author={Minoofar, Amir and Karapetyan, Narek and Almaiman, Ahmed and Zhou, Huibin and Song, Hao and Zou, Kaiheng and Ko, Wing and Ramakrishnan, Muralekrishnan and Annavaram, Murali and Habif, Jonathan L and others},
journal={Optics Letters},
volume={48},
number={17},
pages={4617--4620},
year={2023},
publisher={Optica Publishing Group}
}
Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence.
Yin, Z.; Datta, G.; Kaiser, M. A.; Beerel, P.; Jacob, A.; and Jaiswal, A.
In
2023 IEEE International Conference on Rebooting Computing (ICRC), pages 1-5, 2023.
doi
link
bibtex
@INPROCEEDINGS{10386206,
author={Yin, Zihan and Datta, Gourav and Kaiser, Md Abdullah-Al and Beerel, Peter and Jacob, Ajey and Jaiswal, Akhilesh},
booktitle={2023 IEEE International Conference on Rebooting Computing (ICRC)},
title={Design Considerations for 3D Heterogeneous Integration Driven Analog Processing-in-Pixel for Extreme-Edge Intelligence},
year={2023},
volume={},
number={},
pages={1-5},
keywords={Computer vision;Three-dimensional displays;Multichip modules;CMOS image sensors;Data processing;Trajectory;Circuit synthesis;3D integration;in-pixel computing;edge computing;CMOS image sensors;Cu–Cu connections},
doi={10.1109/ICRC60800.2023.10386206}}
Designing Artificial Intelligence for Open Worlds.
Kejriwal, M.
In
2023 Annual Meeting, 2023. AAAS
link
bibtex
@inproceedings{kejriwal2023designing,
title={Designing Artificial Intelligence for Open Worlds},
author={Kejriwal, Mayank},
booktitle={2023 Annual Meeting},
year={2023},
organization={AAAS}
}
Detecting Semantic Errors in Tables using Textual Evidence.
Pham, M.; Knoblock, C. A.; and Chen, M.
In
2023 IEEE International Conference on Big Data (BigData), pages 292-303, 2023.
doi
link
bibtex
@INPROCEEDINGS{10386632,
author={Pham, Minh and Knoblock, Craig A. and Chen, Muhao},
booktitle={2023 IEEE International Conference on Big Data (BigData)},
title={Detecting Semantic Errors in Tables using Textual Evidence},
year={2023},
volume={},
number={},
pages={292-303},
keywords={Semantics;Self-supervised learning;Syntactics;Big Data;Data models;Semantic error detection;contrastive learning;language models;textual evidence},
doi={10.1109/BigData59044.2023.10386632}}
Detection of laser light scattered from aerosols in a bright background using a balanced coherent receiver.
Belzer, H.; Rittenbach, A.; and Habif, J. L.
Opt. Continuum, 2(4): 751–757. Apr 2023.
Paper
doi
link
bibtex
abstract
@article{Belzer:23,
author = {Helena Belzer and Andrew Rittenbach and Jonathan L. Habif},
journal = {Opt. Continuum},
keywords = {Heterodyne detection; Infrared lasers; Laser light; Laser sources; Near infrared; Tunable lasers},
number = {4},
pages = {751--757},
publisher = {Optica Publishing Group},
title = {Detection of laser light scattered from aerosols in a bright background using a balanced coherent receiver},
volume = {2},
month = {Apr},
year = {2023},
url = {https://opg.optica.org/optcon/abstract.cfm?URI=optcon-2-4-751},
doi = {10.1364/OPTCON.484917},
abstract = {We experimentally demonstrate the detection of laser light, which has been scattered from micron-scale atmospheric particulates, using a balanced heterodyne detection system with a non-cooperative tunable laser as a local oscillator source. The signal generated by the coherent detection receiver is provided to a signal processing algorithm designed to discriminate scattered laser light entering the receiver from the incoherent background and internal receiver noise. A receiver operating characteristic quantifies the performance of the receiver and demonstrates that optical coherence can be used as a parameter for laser detection even after the process of optical scattering from a disordered media.},
}
We experimentally demonstrate the detection of laser light, which has been scattered from micron-scale atmospheric particulates, using a balanced heterodyne detection system with a non-cooperative tunable laser as a local oscillator source. The signal generated by the coherent detection receiver is provided to a signal processing algorithm designed to discriminate scattered laser light entering the receiver from the incoherent background and internal receiver noise. A receiver operating characteristic quantifies the performance of the receiver and demonstrates that optical coherence can be used as a parameter for laser detection even after the process of optical scattering from a disordered media.
Discovering collective narratives shifts in online discussions.
Zhao, W.; Guo, F.; Lerman, K.; and Ahn, Y.
CoRR, abs/2307.08541. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2307-08541,
author = {Wanying Zhao and
Fiona Guo and
Kristina Lerman and
Yong{-}Yeol Ahn},
title = {Discovering collective narratives shifts in online discussions},
journal = {CoRR},
volume = {abs/2307.08541},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2307.08541},
doi = {10.48550/ARXIV.2307.08541},
eprinttype = {arXiv},
eprint = {2307.08541},
timestamp = {Tue, 25 Jul 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2307-08541.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Distributed Edge Machine Learning Pipeline Scheduling with Reverse Auctions.
Imes, C.; King, D. W.; and Walters, J. P.
In
2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC), pages 196-203, 2023.
doi
link
bibtex
@INPROCEEDINGS{PipeEdgeRevAuct,
author={Imes, Connor and King, David W. and Walters, John Paul},
booktitle={2023 Eighth International Conference on Fog and Mobile Edge Computing (FMEC)},
title={Distributed Edge Machine Learning Pipeline Scheduling with Reverse Auctions},
year={2023},
volume={},
number={},
pages={196-203},
doi={10.1109/FMEC59375.2023.10306169},
ISIArea = {ML, CAS}
}
Dynamic FastMap: An Efficient Algorithm for Spatiotemporal Embedding of Dynamic Graphs.
Thakoor, O.; and Thittamaranahalli, S.
Proceedings of the Thirty-Sixth International FLAIRS Conference (FLAIRS-2023). 2023.
link
bibtex
@article{tksk03,
author={Omkar Thakoor and Satish Thittamaranahalli},
title={Dynamic FastMap: An Efficient Algorithm for Spatiotemporal Embedding of Dynamic Graphs},
journal={Proceedings of the Thirty-Sixth International FLAIRS Conference (FLAIRS-2023)},
year={2023}
}
Dynamic Physics-Guided Deep Learning for Production Forecasting in Unconventional Reservoirs.
Mohd Razak, S.; Cornelio, J.; Cho, Y.; Liu, H.; Vaidya, R.; and Jafarpour, B.
In
SPE Western Regional Meeting, pages D021S004R002, 2023. SPE
Paper
link
bibtex
@inproceedings{mohd_razak_dynamic_2023,
title = {Dynamic {Physics}-{Guided} {Deep} {Learning} for {Production} {Forecasting} in {Unconventional} {Reservoirs}},
url = {https://onepetro.org/SPEWRM/proceedings-abstract/23WRM/2-23WRM/519649},
urldate = {2024-02-12},
booktitle = {{SPE} {Western} {Regional} {Meeting}},
publisher = {SPE},
author = {Mohd Razak, Syamil and Cornelio, Jodel and Cho, Young and Liu, Hui-Hai and Vaidya, Ravimadhav and Jafarpour, Behnam},
year = {2023},
pages = {D021S004R002},
}
Dynamic Study of Intercalation/Deintercalation of Ionic Liquids in Multilayer Graphene Using an Alternating Current Raman Spectroscopy Technique.
Cai, Z.; Weinstein, H.; Aravind, I.; Li, R.; Weng, S.; Zhang, B.; Habif, J. L; and Cronin, S. B
The Journal of Physical Chemistry Letters, 14(32): 7223–7228. 2023.
link
bibtex
@article{cai2023dynamic,
title={Dynamic Study of Intercalation/Deintercalation of Ionic Liquids in Multilayer Graphene Using an Alternating Current Raman Spectroscopy Technique},
author={Cai, Zhi and Weinstein, Haley and Aravind, Indu and Li, Ruoxi and Weng, Sizhe and Zhang, Boxin and Habif, Jonathan L and Cronin, Stephen B},
journal={The Journal of Physical Chemistry Letters},
volume={14},
number={32},
pages={7223--7228},
year={2023},
publisher={ACS Publications}
}
Dynamic Study of Intercalation/Deintercalation of Ionic Liquids in Multilayer Graphene Using an Alternating Current Raman Spectroscopy Technique.
Zhi Cai, H. W.; and Cronin, S. B.
The Journal of Physical Chemistry Letters, 14(32): 7223-7228. Aug 2023.
Paper
doi
link
bibtex
@Article{Cai2023,
author={Zhi Cai, Haley Weinstein, Indu Aravind, Ruoxi Li, Sizhe Weng, Boxin Zhang, Jonathan L. Habif, and Stephen B. Cronin},
title={Dynamic Study of Intercalation/Deintercalation of Ionic Liquids in Multilayer Graphene Using an Alternating Current Raman Spectroscopy Technique},
journal={The Journal of Physical Chemistry Letters},
year={2023},
month={Aug},
day={17},
publisher={American Chemical Society},
volume={14},
number={32},
pages={7223-7228},
doi={10.1021/acs.jpclett.3c01686},
url={https://doi.org/10.1021/acs.jpclett.3c01686}
}
Effectiveness of Nonpharmaceutical Interventions to Avert the Second COVID-19 Surge in Los Angeles County: A Simulation Study.
Rodier, C.; Horn, A.; Zhang, Y.; Kaddoura, I.; and Müller, S.
. 2023.
Paper
link
bibtex
@article{rodier2023effectiveness,
title={Effectiveness of Nonpharmaceutical Interventions to Avert the Second COVID-19 Surge in Los Angeles County: A Simulation Study},
author={Rodier, Caroline and Horn, Abigail and Zhang, Yunwan and Kaddoura, Ihab and M{\"u}ller, Sebastian},
year={2023},
url={https://escholarship.org/uc/item/5f78h654}
}
Efficient Methods for Natural Language Processing: A Survey.
Treviso, M.; Lee, J.; Ji, T.; van Aken, B.; Cao, Q.; Ciosici, M. R.; Hassid, M.; Heafield, K.; Hooker, S.; Raffel, C.; Martins, P. H.; Martins, A. F. T.; Forde, J. Z.; Milder, P.; Simpson, E.; Slonim, N.; Dodge, J.; Strubell, E.; Balasubramanian, N.; Derczynski, L.; Gurevych, I.; and Schwartz, R.
Transactions of the Association for Computational Linguistics, 11: 826–860. 2023.
Paper
doi
link
bibtex
abstract
@article{treviso-etal-2023-efficient,
abstract = {Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources include data, time, storage, or energy, all of which are naturally limited and unevenly distributed. This motivates research into efficient methods that require fewer resources to achieve similar results. This survey synthesizes and relates current methods and findings in efficient NLP. We aim to provide both guidance for conducting NLP under limited resources, and point towards promising research directions for developing more efficient methods.},
address = {Cambridge, MA},
author = {Treviso, Marcos and Lee, Ji-Ung and Ji, Tianchu and van Aken, Betty and Cao, Qingqing and Ciosici, Manuel R. and Hassid, Michael and Heafield, Kenneth and Hooker, Sara and Raffel, Colin and Martins, Pedro H. and Martins, Andr{\'e} F. T. and Forde, Jessica Zosa and Milder, Peter and Simpson, Edwin and Slonim, Noam and Dodge, Jesse and Strubell, Emma and Balasubramanian, Niranjan and Derczynski, Leon and Gurevych, Iryna and Schwartz, Roy},
date-added = {2024-01-29 13:18:11 -0800},
date-modified = {2024-01-29 13:18:11 -0800},
doi = {10.1162/tacl_a_00577},
journal = {Transactions of the Association for Computational Linguistics},
pages = {826--860},
publisher = {MIT Press},
title = {Efficient Methods for Natural Language Processing: A Survey},
url = {https://aclanthology.org/2023.tacl-1.48},
volume = {11},
year = {2023},
bdsk-url-1 = {https://aclanthology.org/2023.tacl-1.48},
bdsk-url-2 = {https://doi.org/10.1162/tacl_a_00577}}
Recent work in natural language processing (NLP) has yielded appealing results from scaling model parameters and training data; however, using only scale to improve performance means that resource consumption also grows. Such resources include data, time, storage, or energy, all of which are naturally limited and unevenly distributed. This motivates research into efficient methods that require fewer resources to achieve similar results. This survey synthesizes and relates current methods and findings in efficient NLP. We aim to provide both guidance for conducting NLP under limited resources, and point towards promising research directions for developing more efficient methods.
Efficient Multi-Query Bi-Objective Search via Contraction Hierarchies.
Zhang, H.; Salzman, O.; Felner, A.; Thittamaranahalli, S.; Hernandez, C.; and Koenig, S.
Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS-2023). 2023.
link
bibtex
@article{tksk01,
author={Han Zhang and Oren Salzman and Ariel Felner and Satish Thittamaranahalli and Carlos Hernandez and Sven Koenig},
title={Efficient Multi-Query Bi-Objective Search via Contraction Hierarchies},
journal={Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS-2023)},
year={2023}
}
Efficient Multi-Query Bi-Objective Search via Contraction Hierarchies.
Zhang, H.; Salzman, O.; Felner, A.; Thittamaranahalli, S.; Hernandez, C.; and Koenig, S.
Proceedings of the First International Workshop on Search and Planning with Complex Objectives (WoSePCO-2023). 2023.
link
bibtex
@article{tksk07,
author={Han Zhang and Oren Salzman and Ariel Felner and Satish Thittamaranahalli and Carlos Hernandez and Sven Koenig},
title={Efficient Multi-Query Bi-Objective Search via Contraction Hierarchies},
journal={Proceedings of the First International Workshop on Search and Planning with Complex Objectives (WoSePCO-2023)},
year={2023}
}
Efficient Porting of FPGA Independent Testing Within and Across Vendors.
Haroldsen, T.; Sung, T.; Shears, O.; Glick, D.; and Danner, J.
In
Government Microcircuit Applications and Critical Technology Conference, March 2023.
link
bibtex
@inproceedings{cift-gomac:2023,
author = {T. Haroldsen and T.Y. Sung and O. Shears and D. Glick and J. Danner},
title = {{Efficient Porting of FPGA Independent Testing Within and Across Vendors}},
booktitle = {Government Microcircuit Applications and Critical Technology Conference},
month = {March},
year = {2023},
}
Efficient Porting of FPGA independent Testing Within and Across Vendors.
Travis Haroldsen, T. S.; and Osaze Shears, D. G.
In
GOMACTech-23, 2023.
link
bibtex
@InProceedings{ Haroldsen-2023,
author = {Travis Haroldsen, Ting-Yuan Sung, Osaze Shears, Dallon Glick, Jay Danner},
title = {Efficient Porting of FPGA independent Testing Within and Across Vendors},
booktitle = {GOMACTech-23},
year = {2023},
ISIArea = {CAS}
}
Elephants Sharing the Highway: Studying TCP Fairness in Large Transfers over High Throughput Links.
Mahmud, I.; Papadimitriou, G.; Wang, C.; Kiran, M.; Mandal, A.; and Deelman, E.
In
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis, of
SC-W '23, pages 806–818, New York, NY, USA, 2023. Association for Computing Machinery
Funding Acknowledgments: DOE DE-SC0022328. Best Paper Award.
Paper
doi
link
bibtex
@InProceedings{ mahmud-indis-2023,
Author = {Mahmud, Imtiaz and Papadimitriou, George and Wang, Cong
and Kiran, Mariam and Mandal, Anirban and Deelman, Ewa},
Title = {Elephants Sharing the Highway: Studying TCP Fairness in
Large Transfers over High Throughput Links},
Year = {2023},
ISBN = {9798400707858},
Publisher = {Association for Computing Machinery},
Address = {New York, NY, USA},
URL = {https://doi.org/10.1145/3624062.3624594},
DOI = {10.1145/3624062.3624594},
BookTitle = {Proceedings of the SC '23 Workshops of The International
Conference on High Performance Computing, Network, Storage,
and Analysis},
Pages = {806–818},
numpages = {13},
Keywords = {Buffer Size, FABRIC, High-Speed Internet, TCP Congestion
Control, Elephant Flows, Active Queue Management,
High-Bandwidth, Fairness},
Location = {Denver, CO, USA},
Series = {SC-W '23},
Note = {Funding Acknowledgments: DOE DE-SC0022328. Best Paper
Award.}
}
End-to-end Integration of Scientific Workflows on Distributed Cyberinfrastructures: Challenges and Lessons Learned with an Earth Science Application.
Roa, C.; Rynge, M.; Olaya, P.; Vahi, K.; Miller, T.; Goodhue, J.; Griffioen, J.; Hudak, D.; Knuth, S.; Llamas, R.; Vargas, R.; Livny, M.; Deelman, E.; and Taufer, M.
In
2023 IEEE/ACM 16th International Conference on Utility and Cloud Computing (UCC), of
UCC '23, 2023.
link
bibtex
@InProceedings{ roa-ucc-2023,
Author = {Roa, Camila and Rynge, Mats and Olaya, Paula and Vahi,
Karan and Miller, Todd and Goodhue, John and Griffioen,
James and Hudak, David and Knuth, Shelley and Llamas,
Ricardo and Vargas, Rodrigo and Livny, Miron, and Deelman,
Ewa and Taufer, Michela},
Title = {End-to-end Integration of Scientific Workflows on
Distributed Cyberinfrastructures: Challenges and Lessons
Learned with an Earth Science Application},
Year = {2023},
BookTitle = {2023 IEEE/ACM 16th International Conference on Utility and
Cloud Computing (UCC)},
Location = {Taormina (Messina), Italy},
Series = {UCC '23}
}
Evaluating Large Language Models on Controlled Generation Tasks.
Sun, J.; Tian, Y.; Zhou, W.; Xu, N.; Hu, Q.; Gupta, R.; Wieting, J.; Peng, N.; and Ma, X.
In
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 3155–3168, Singapore, December 2023. Association for Computational Linguistics
link
bibtex
@inproceedings{sun-etal-2023-evaluating,
title = "Evaluating Large Language Models on Controlled Generation Tasks",
author = "Sun, Jiao and Tian, Yufei and Zhou, Wangchunshu and Xu, Nan and Hu, Qian and Gupta, Rahul
and Wieting, John and Peng, Nanyun and Ma, Xuezhe",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
pages = "3155--3168",
}
Evaluating deep generative models on cognitive tasks: a case study.
Tang, Z.; and Kejriwal, M.
Discover Artificial Intelligence, 3(1): 21. 2023.
link
bibtex
@article{tang2023evaluating,
title={Evaluating deep generative models on cognitive tasks: a case study},
author={Tang, Zhisheng and Kejriwal, Mayank},
journal={Discover Artificial Intelligence},
volume={3},
number={1},
pages={21},
year={2023},
publisher={Springer}
}
Evaluation of transfer learning methods for detecting Alzheimer’s disease with brain MRI.
Dhinagar, N. J.; Thomopoulos, S. I.; Rajagopalan, P.; Stripelis, D.; Ambite, J. L.; Steeg, G. V.; and Thompson, P. M.
In volume 12567, pages 504–513, 3 2023. SPIE
[Online; accessed 2023-04-18]
Paper
doi
link
bibtex
@inproceedings{dhinagar2023:sipaim,
journal={18th International Symposium on Medical Information Processing and Analysis},
doi={10.1117/12.2670457},
publisher={SPIE},
title={Evaluation of transfer learning methods for detecting Alzheimer’s disease with brain MRI},
url={https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12567/125671L/Evaluation-of-transfer-learning-methods-for-detecting-Alzheimers-disease-with/10.1117/12.2670457.full},
volume=12567,
author={Dhinagar, Nikhil J. and Thomopoulos, Sophia I. and Rajagopalan, Priya and Stripelis, Dimitris and Ambite, Jose Luis and Steeg, Greg Ver and Thompson, Paul M.},
note={[Online; accessed 2023-04-18]},
pages={504--513},
date={2023-03-06},
year=2023,
month=3,
day=6,
}
Experimental Observation of Thermalization with Noncommuting Charges.
Kranzl, F.; Lasek, A.; Joshi, M. K.; Kalev, A.; Blatt, R.; Roos, C. F.; and Yunger Halpern, N.
PRX Quantum, 4: 020318. Apr 2023.
Paper
doi
link
bibtex
@article{PRXQuantum.4.020318,
title = {Experimental Observation of Thermalization with Noncommuting Charges},
author = {Kranzl, Florian and Lasek, Aleksander and Joshi, Manoj K. and Kalev, Amir and Blatt, Rainer and Roos, Christian F. and Yunger Halpern, Nicole},
journal = {PRX Quantum},
volume = {4},
issue = {2},
pages = {020318},
numpages = {19},
year = {2023},
month = {Apr},
publisher = {American Physical Society},
doi = {10.1103/PRXQuantum.4.020318},
url = {https://link.aps.org/doi/10.1103/PRXQuantum.4.020318}
}
Experimental demonstration of an optics-based 4-PSK half-adder using nonlinear wave mixing.
Song, H.; Zou, K.; Zhou, H.; Karapetyan, N.; Minoofar, A.; Su, X.; Almaiman, A.; Habif, J. L; Tur, M.; and Willner, A. E
Optics Letters, 48(13): 3475–3478. 2023.
link
bibtex
@article{song2023experimental,
title={Experimental demonstration of an optics-based 4-PSK half-adder using nonlinear wave mixing},
author={Song, Hao and Zou, Kaiheng and Zhou, Huibin and Karapetyan, Narek and Minoofar, Amir and Su, Xinzhou and Almaiman, Ahmed and Habif, Jonathan L and Tur, Moshe and Willner, Alan E},
journal={Optics Letters},
volume={48},
number={13},
pages={3475--3478},
year={2023},
publisher={Optica Publishing Group}
}
Experiments on Network Services for Video Transmission using FABRIC Instrument Resources.
Morel, A. E.; Gafurov, D.; Calyam, P.; Wang, C.; Thareja, K.; Mandal, A.; Lyons, E.; Zink, M.; Papadimitriou, G.; and Deelman, E.
In
IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS), pages 1-6, 2023.
Funding Acknowledgments: NSF CNS-1950873, CNS-1647182 and OAC-2018074
doi
link
bibtex
@InProceedings{ morel-infocom-2023,
Author = {Morel, Alicia Esquivel and Gafurov, Durbek and Calyam,
Prasad and Wang, Cong and Thareja, Komal and Mandal,
Anirban and Lyons, Eric and Zink, Michael and
Papadimitriou, George and Deelman, Ewa},
BookTitle = {IEEE INFOCOM 2023 - IEEE Conference on Computer
Communications Workshops (INFOCOM WKSHPS)},
Title = {Experiments on Network Services for Video Transmission
using FABRIC Instrument Resources},
Year = {2023},
Volume = {},
Number = {},
Pages = {1-6},
DOI = {10.1109/INFOCOMWKSHPS57453.2023.10225817},
Note = {Funding Acknowledgments: NSF CNS-1950873, CNS-1647182 and
OAC-2018074}
}
Explainable Classification of Internet Memes.
Thakur, A. K.; Ilievski, F.; Sandlin, H.; Sourati, Z.; Luceri, L.; Tommasini, R.; and Mermoud, A.
In
NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning, 2023.
link
bibtex
@inproceedings{thakur2023explainable,
title={Explainable Classification of Internet Memes},
author={Thakur, Abhinav Kumar and Ilievski, Filip and Sandlin, H{\^o}ng-{\^A}n and Sourati, Zhivar and Luceri, Luca and Tommasini, Riccardo and Mermoud, Alain},
booktitle={NeSy 2023, 17th International Workshop on Neural-Symbolic Learning and Reasoning},
year={2023}
}
Faithful Persona-based Conversational Dataset Generation with Large Language Models.
Jandaghi, P.; Sheng, X.; Bai, X.; Pujara, J.; and Sidahmed, H.
2023.
link
bibtex
@unpublished{jandaghi:arxiv23,
author = "Jandaghi, Pegah and Sheng, XiangHai and Bai, Xinyi and Pujara, Jay and Sidahmed, Hakim",
arxiv_url = "https://arxiv.org/pdf/2310.03051.pdf",
sec = "preprint",
title = "Faithful Persona-based Conversational Dataset Generation with Large Language Models",
year = "2023"
}
Fast Quantum State Reconstruction via Accelerated Non-Convex Programming.
Kim, J. L.; Kollias, G.; Kalev, A.; Wei, K. X.; and Kyrillidis, A.
Photonics, 10(2). 2023.
Paper
doi
link
bibtex
@Article{photonics10020116,
AUTHOR = {Kim, Junhyung Lyle and Kollias, George and Kalev, Amir and Wei, Ken X. and Kyrillidis, Anastasios},
TITLE = {Fast Quantum State Reconstruction via Accelerated Non-Convex Programming},
JOURNAL = {Photonics},
VOLUME = {10},
YEAR = {2023},
NUMBER = {2},
ARTICLE-NUMBER = {116},
URL = {https://www.mdpi.com/2304-6732/10/2/116},
ISSN = {2304-6732},
DOI = {10.3390/photonics10020116}
}
%%%%%% YEAR 2021%%%%%%%%
FastMapSVM for Predicting CSP Satisfiability.
Zheng, K.; Li, A.; Zhang, H.; and Thittamaranahalli, S.
Proceedings of the Twenty-Ninth International Conference on Principles and Practice of Constraint Programming (CP-2023). 2023.
link
bibtex
@article{tksk09,
author={Kexin Zheng and Ang Li and Han Zhang and Satish Thittamaranahalli},
title={FastMapSVM for Predicting CSP Satisfiability},
journal={Proceedings of the Twenty-Ninth International Conference on Principles and Practice of Constraint Programming (CP-2023)},
year={2023}
}
Feature Interpretation using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNNs Learned Features.
Hasenstab, K. A; Huynh, J.; Masoudi, S.; Cunha, G. M; Pazzani, M.; and Hsiao, A.
IEEE Access. 2023.
link
bibtex
@article{hasenstab2023feature,
title={Feature Interpretation using Generative Adversarial Networks (FIGAN): A Framework for Visualizing a CNNs Learned Features},
author={Hasenstab, Kyle A and Huynh, Justin and Masoudi, Samira and Cunha, Guilherme M and Pazzani, Michael and Hsiao, Albert},
journal={IEEE Access},
year={2023},
publisher={IEEE}
}
FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System.
Jin, W.; Yao, Y.; Han, S.; Joe-Wong, C.; Ravi, S.; Avestimehr, S.; and He, C.
CoRR, abs/2303.10837. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2303-10837,
author = {Weizhao Jin and
Yuhang Yao and
Shanshan Han and
Carlee Joe{-}Wong and
Srivatsan Ravi and
Salman Avestimehr and
Chaoyang He},
title = {FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving
Federated Learning System},
journal = {CoRR},
volume = {abs/2303.10837},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2303.10837},
doi = {10.48550/ARXIV.2303.10837},
eprinttype = {arXiv},
eprint = {2303.10837},
timestamp = {Wed, 22 Mar 2023 14:41:36 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2303-10837.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Federated Deep Learning for Detecting Alzheimer’s Disease in Multi-Cohort Brain MRI.
Stripelis, D.; Dhinagar, N. J; Romero, R. V. S.; Thomopoulos, S. I; Thompson, P. M; and Ambite, J. L.
Alzheimer's & Dementia, 19(S1): e065998. 2023.
_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/alz.065998
Paper
doi
link
bibtex
@article{stripelis2023:AD,
title = {Federated {Deep} {Learning} for {Detecting} {Alzheimer}’s {Disease} in {Multi}-{Cohort} {Brain} {MRI}},
volume = {19},
copyright = {© 2023 the Alzheimer's Association.},
issn = {1552-5279},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/alz.065998},
doi = {10.1002/alz.065998},
language = {en},
number = {S1},
urldate = {2024-01-27},
journal = {Alzheimer's \& Dementia},
author = {Stripelis, Dimitris and Dhinagar, Nikhil J and Romero, Rafael V. Sanchez and Thomopoulos, Sophia I and Thompson, Paul M and Ambite, Jose Luis},
year = {2023},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/alz.065998},
pages = {e065998},
file = {Snapshot:/Users/ambite/Zotero/storage/NRYZMLVB/alz.html:text/html},
}
Federated Learning over Harmonized Data Silos.
Stripelis, D.; and Ambite, J. L.
In
7th International Workshop on Health Intelligence (W3PHIAI-23), Washington, D.C., 2023. AAAI
link
bibtex
@InProceedings{stripelis2023:W3PHIAI,
author = {Dimitris Stripelis and Jos\'{e} Luis Ambite},
title = {Federated Learning over Harmonized Data Silos},
booktitle = {7th International Workshop on Health Intelligence {(W3PHIAI-23)}},
year = {2023},
address = {Washington, D.C.},
organization = {AAAI},
}
Feedback Loops and Complex Dynamics of Harmful Speech in Online Discussions.
Chang, R.; May, J.; and Lerman, K.
In Thomson, R.; Al-khateeb, S.; Burger, A.; Park, P. S.; and Pyke, A. A., editor(s),
Social, Cultural, and Behavioral Modeling - 16th International Conference, SBP-BRiMS 2023, Pittsburgh, PA, USA, September 20-22, 2023, Proceedings, volume 14161, of
Lecture Notes in Computer Science, pages 85–94, 2023. Springer
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/sbp/ChangML23,
author = {Rong{-}Ching Chang and
Jonathan May and
Kristina Lerman},
editor = {Robert Thomson and
Samer Al{-}khateeb and
Annetta Burger and
Patrick S. Park and
Aryn A. Pyke},
title = {Feedback Loops and Complex Dynamics of Harmful Speech in Online Discussions},
booktitle = {Social, Cultural, and Behavioral Modeling - 16th International Conference,
SBP-BRiMS 2023, Pittsburgh, PA, USA, September 20-22, 2023, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {14161},
pages = {85--94},
publisher = {Springer},
year = {2023},
url = {https://doi.org/10.1007/978-3-031-43129-6\_9},
doi = {10.1007/978-3-031-43129-6\_9},
timestamp = {Tue, 07 May 2024 01:00:00 +0200},
biburl = {https://dblp.org/rec/conf/sbp/ChangML23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Feedback Loops andComplex Dynamics ofHarmful Speech inOnline Discussions.
Chang, R.; May, J.; and Lerman, K.
In
Social, Cultural, and Behavioral Modeling: 16th International Conference, SBP-BRiMS 2023, Pittsburgh, PA, USA, September 20–22, 2023, Proceedings, pages 85–94, Berlin, Heidelberg, 2023. Springer-Verlag
Paper
doi
link
bibtex
abstract
@inproceedings{10.1007/978-3-031-43129-6_9,
author = {Chang, Rong-Ching and May, Jonathan and Lerman, Kristina},
title = {Feedback Loops and Complex Dynamics of Harmful Speech in Online Discussions},
year = {2023},
isbn = {978-3-031-43128-9},
publisher = {Springer-Verlag},
address = {Berlin, Heidelberg},
url = {https://doi.org/10.1007/978-3-031-43129-6_9},
doi = {10.1007/978-3-031-43129-6_9},
abstract = {Harmful and toxic speech contribute to an unwelcoming online environment that suppresses participation and conversation. Efforts have focused on detecting and mitigating harmful speech; however, the mechanisms by which toxicity degrades online discussions are not well understood. This paper makes two contributions. First, to comprehensively model harmful comments, we introduce a multilingual misogyny and sexist speech detection model (). Second, we model the complex dynamics of online discussions as feedback loops in which harmful comments lead to negative emotions which prompt even more harmful comments. To quantify the feedback loops, we use a combination of mutual Granger causality and regression to analyze discussions on two political forums on Reddit: the moderated political forum r/Politics and the moderated neutral political forum r/NeutralPolitics. Our results suggest that harmful comments and negative emotions create self-reinforcing feedback loops in forums. Contrarily, moderation with neutral discussion appears to tip interactions into self-extinguishing feedback loops that reduce harmful speech and negative emotions. Our study sheds more light on the complex dynamics of harmful speech and the role of moderation and neutral discussion in mitigating these dynamics.},
booktitle = {Social, Cultural, and Behavioral Modeling: 16th International Conference, SBP-BRiMS 2023, Pittsburgh, PA, USA, September 20–22, 2023, Proceedings},
pages = {85–94},
numpages = {10},
keywords = {Feedback Loop, Moderation, Granger Causality},
location = {Pittsburgh, PA, USA}
}
Harmful and toxic speech contribute to an unwelcoming online environment that suppresses participation and conversation. Efforts have focused on detecting and mitigating harmful speech; however, the mechanisms by which toxicity degrades online discussions are not well understood. This paper makes two contributions. First, to comprehensively model harmful comments, we introduce a multilingual misogyny and sexist speech detection model (). Second, we model the complex dynamics of online discussions as feedback loops in which harmful comments lead to negative emotions which prompt even more harmful comments. To quantify the feedback loops, we use a combination of mutual Granger causality and regression to analyze discussions on two political forums on Reddit: the moderated political forum r/Politics and the moderated neutral political forum r/NeutralPolitics. Our results suggest that harmful comments and negative emotions create self-reinforcing feedback loops in forums. Contrarily, moderation with neutral discussion appears to tip interactions into self-extinguishing feedback loops that reduce harmful speech and negative emotions. Our study sheds more light on the complex dynamics of harmful speech and the role of moderation and neutral discussion in mitigating these dynamics.
First Steps Towards a Source Recommendation Engine: Investigating How Sources Are Used in News Articles.
Zurich, Switzerland, June 2023.
Paper
link
bibtex
@Proceedings{spangher23.djc,
title = {First Steps Towards a Source Recommendation Engine:
Investigating How Sources Are Used in News Articles},
year = 2023,
url={https://www.datajconf.com/papers/CJ_DataJConf_2023_paper_74.pdf},
booktitle = {Proc. The Joint Computation + Journalism European Data \& Computational Journalism Conference},
address = {Zurich, Switzerland},
month = {June}}
Flow-Bench: A Dataset for Computational Workflow Anomaly Detection.
Papadimitriou, G.; Jin, H.; Wang, C.; Raghavan, K.; Mandal, A.; Balaprakash, P.; and Deelman, E.
. 2023.
Paper
doi
link
bibtex
@Article{ flow-bench,
Author = {Papadimitriou, George and Jin, Hongwei and Wang, Cong and
Raghavan, Krishnan and Mandal, Anirban and Balaprakash,
Prasanna and Deelman, Ewa},
Title = {Flow-Bench: A Dataset for Computational Workflow Anomaly
Detection},
Publisher = {arXiv},
Year = {2023},
DOI = {10.48550/ARXIV.2306.09930},
URL = {https://arxiv.org/abs/2306.09930},
copyright = {arXiv.org perpetual, non-exclusive license}
}
FlyNet: Drones on the Horizon.
Morel, A. E.; Qu, C.; Calyam, P.; Wang, C.; Thareja, K.; Mandal, A.; Lyons, E.; Zink, M.; Papadimitriou, G.; and Deelman, E.
IEEE Internet Computing, 27(3): 35-43. 2023.
Funding Acknowledgments: NSF 1950873, 1647182, 2018074
doi
link
bibtex
@Article{ morel-mic-2023,
Author = {Morel, Alicia Esquivel and Qu, Chengyi and Calyam, Prasad
and Wang, Cong and Thareja, Komal and Mandal, Anirban and
Lyons, Eric and Zink, Michael and Papadimitriou, George and
Deelman, Ewa},
Journal = {IEEE Internet Computing},
Title = {FlyNet: Drones on the Horizon},
Year = {2023},
Volume = {27},
Number = {3},
Pages = {35-43},
DOI = {10.1109/MIC.2023.3260440},
Note = {Funding Acknowledgments: NSF 1950873, 1647182, 2018074}
}
FlyPaw: Optimized Route Planning for Scientific UAVMissions.
Grote, A.; Lyons, E.; Thareja, K.; Papadimitriou, G.; Deelman, E.; Mandal, A.; Calyam, P.; and Zink, M.
In
2023 IEEE 19th International Conference on e-Science (e-Science), pages 1-10, 2023.
Funding Acknowledgments: NSF 2018074, 1939334
doi
link
bibtex
@InProceedings{ grote-escience-2023,
Author = {Grote, Andrew and Lyons, Eric and Thareja, Komal and
Papadimitriou, George and Deelman, Ewa and Mandal, Anirban
and Calyam, Prasad and Zink, Michael},
BookTitle = {2023 IEEE 19th International Conference on e-Science
(e-Science)},
Title = {FlyPaw: Optimized Route Planning for Scientific
UAVMissions},
Year = {2023},
Volume = {},
Number = {},
Pages = {1-10},
DOI = {10.1109/e-Science58273.2023.10254831},
Note = {Funding Acknowledgments: NSF 2018074, 1939334}
}
Gender and Prestige Bias in Coronavirus News Reporting.
Dorn, R.; Ma, Y.; Morstatter, F.; and Lerman, K.
CoRR, abs/2301.11994. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2301-11994,
author = {Rebecca Dorn and
Yiwen Ma and
Fred Morstatter and
Kristina Lerman},
title = {Gender and Prestige Bias in Coronavirus News Reporting},
journal = {CoRR},
volume = {abs/2301.11994},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2301.11994},
doi = {10.48550/ARXIV.2301.11994},
eprinttype = {arXiv},
eprint = {2301.11994},
timestamp = {Tue, 31 Jan 2023 00:00:00 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2301-11994.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
GeoAI for the Digitization of Historical Maps.
Chiang, Y.; Chen, M.; Duan, W.; Kim, J.; Knoblock, C. A; Leyk, S.; Li, Z.; Lin, Y.; Namgung, M.; Shbita, B.; and Uhl, J. H
In Gao, S.; Hu, Y.; and Li, W., editor(s),
Handbook of Geospatial Artificial Intelligence, pages 217–247. CRC Press, 2023.
Link
link
bibtex
13 downloads
@incollection{chiang2023geoai,
title={GeoAI for the Digitization of Historical Maps},
author={Chiang, Yao-Yi and Chen, Muhao and Duan, Weiwei and Kim, Jina and Knoblock, Craig A and Leyk, Stefan and Li, Zekun and Lin, Yijun and Namgung, Min and Shbita, Basel and Uhl, Johannes H},
booktitle={Handbook of Geospatial Artificial Intelligence},
editor={Gao, Song and Hu, Yingjie and Li, Wenwen},
pages={217--247},
year={2023},
publisher={CRC Press},
urlLink={https://doi.org/10.1201/9781003308423-11}
}
Graph neural networks for detecting anomalies in scientific workflows.
Jin, H.; Raghavan, K.; Papadimitriou, G.; Wang, C.; Mandal, A.; Kiran, M.; Deelman, E.; and Balaprakash, P.
The International Journal of High Performance Computing Applications. 2023.
Funding Acknowledgments: DOE DE-SC0022328, DE-AC02-06CH11357
Paper
doi
link
bibtex
@Article{ jin-ijhpca-2023,
Author = {Hongwei Jin and Krishnan Raghavan and George Papadimitriou
and Cong Wang and Anirban Mandal and Mariam Kiran and Ewa
Deelman and Prasanna Balaprakash},
Title = {Graph neural networks for detecting anomalies in
scientific workflows},
Journal = {The International Journal of High Performance Computing
Applications},
Volume = {},
Number = {},
Pages = {},
Year = {2023},
DOI = {10.1177/10943420231172140},
URL = {https://doi.org/10.1177/10943420231172140},
EPrint = {https://doi.org/10.1177/10943420231172140},
Note = {Funding Acknowledgments: DOE DE-SC0022328,
DE-AC02-06CH11357}
}
Graph-Based Structure Aware Citation Intent Classification.
Du, X.; Ahrabian, K.; Ananthan, A. B. S.; Myloth, R. D.; and Pujara, J.
In
Workshop on Scientific Document Understanding at AAAI, 2023.
link
bibtex
@inproceedings{du:aaai23ws,
Author = "Du, Xinwei and Ahrabian, Kian and Ananthan, Arun Baalaaji Sankar and Myloth, Richard Delwin and Pujara, Jay",
bib_url = "/pubs/bib/du-aaai23ws.bib",
booktitle = "Workshop on Scientific Document Understanding at AAAI",
pdf_url = "/pubs/2023/du-aaai23ws/du-aaai23ws.pdf",
sec = "ws",
title = "Graph-Based Structure Aware Citation Intent Classification",
year = "2023"
}
HALO: An Ontology for Representing Hallucinations in Generative Models.
Nananukul, N.; and Kejriwal, M.
arXiv preprint arXiv:2312.05209. 2023.
link
bibtex
@article{nananukul2023halo,
title={HALO: An Ontology for Representing Hallucinations in Generative Models},
author={Nananukul, Navapat and Kejriwal, Mayank},
journal={arXiv preprint arXiv:2312.05209},
year={2023}
}
HISDAC-ES: historical settlement data compilation for Spain (1900–2020).
Uhl, J. H.; Royé, D.; Burghardt, K.; Aldrey Vázquez, J. A.; Borobio Sanchiz, M.; and Leyk, S.
Earth System Science Data, 15(10): 4713–4747. 2023.
Paper
doi
link
bibtex
@article{Uhl2023_hisdaces,
author = {Uhl, J. H. and Roy\'e, D. and Burghardt, K. and Aldrey V\'azquez, J. A. and Borobio Sanchiz, M. and Leyk, S.},
doi = {10.5194/essd-15-4713-2023},
journal = {Earth System Science Data},
number = {10},
pages = {4713--4747},
title = {HISDAC-ES: historical settlement data compilation for Spain (1900--2020)},
url = {https://essd.copernicus.org/articles/15/4713/2023/},
volume = {15},
year = {2023},
bdsk-url-1 = {https://essd.copernicus.org/articles/15/4713/2023/},
bdsk-url-2 = {https://doi.org/10.5194/essd-15-4713-2023}}
Harvesting Planck radiation for free-space optical communications in the LWIR band.
Haley Weinstein, Z. C.; and Habif, J. L.
In
APS March Meeting Abstracts, volume 2023, of
APS Meeting Abstracts, 2023.
Paper
link
bibtex
@inproceedings{Graphene_Device_2023_March_Meeting,
author = {Haley Weinstein, Zhi Cai, Stephen Cronin, and Jonathan L. Habif},
booktitle = {APS March Meeting Abstracts},
year = 2023,
series = {APS Meeting Abstracts},
volume = {2023},
title = {Harvesting Planck radiation for free-space optical communications in the LWIR band},
year = {2023},
url = {https://meetings.aps.org/Meeting/MAR23/Session/N42.10},
}
How FaR Are Large Language Models From Agents with Theory-of-Mind?.
Zhou, P.; Madaan, A.; Potharaju, S. P.; Gupta, A.; McKee, K. R.; Holtzman, A.; Pujara, J.; Ren, X.; Mishra, S.; Nematzadeh, A.; Upadhyay, S.; and Faruqui, M.
2023.
link
bibtex
@unpublished{zhou:arxiv23,
author = "Zhou, Pei and Madaan, Aman and Potharaju, Srividya Pranavi and Gupta, Aditya and McKee, Kevin R. and Holtzman, Ari and Pujara, Jay and Ren, Xiang and Mishra, Swaroop and Nematzadeh, Aida and Upadhyay, Shyam and Faruqui, Manaal",
arxiv_url = "https://arxiv.org/pdf/2310.03051.pdf",
sec = "preprint",
title = "How FaR Are Large Language Models From Agents with Theory-of-Mind?",
year = "2023"
}
How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events.
Pierri, F.; Luceri, L.; Chen, E.; and Ferrara, E.
EPJ Data Science, 12(1): 43. 2023.
link
bibtex
@article{pierri2023does,
title={How does Twitter account moderation work? Dynamics of account creation and suspension on Twitter during major geopolitical events},
author={Pierri, Francesco and Luceri, Luca and Chen, Emily and Ferrara, Emilio},
journal={EPJ Data Science},
volume={12},
number={1},
pages={43},
year={2023},
publisher={Springer Berlin Heidelberg}
}
How is Artificial Intelligence Changing Science?.
Deelman, E.
In
2023 IEEE 19th International Conference on e-Science (e-Science), pages 1-4, 2023.
Funding Acknowledgments: DOE DE-SC0022328 and NSF 1664162, 2138286
doi
link
bibtex
@InProceedings{ deelman-escience-2023,
Author = {Deelman, Ewa},
BookTitle = {2023 IEEE 19th International Conference on e-Science
(e-Science)},
Title = {How is Artificial Intelligence Changing Science?},
Year = {2023},
Volume = {},
Number = {},
Pages = {1-4},
DOI = {10.1109/e-Science58273.2023.10254913},
Note = {Funding Acknowledgments: DOE DE-SC0022328 and NSF 1664162,
2138286}
}
Hybrid forecasting of geopolitical events.
Benjamin, D. M; Morstatter, F.; Abbas, A. E; Abeliuk, A.; Atanasov, P.; Bennett, S.; Beger, A.; Birari, S.; Budescu, D. V; Catasta, M.; and others
AI Magazine. 2023.
link
bibtex
@article{benjamin2023hybrid,
title={Hybrid forecasting of geopolitical events},
author={Benjamin, Daniel M and Morstatter, Fred and Abbas, Ali E and Abeliuk, Andres and Atanasov, Pavel and Bennett, Stephen and Beger, Andreas and Birari, Saurabh and Budescu, David V and Catasta, Michele and others},
journal={AI Magazine},
year={2023}
}
I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons.
Zhou, P.; Zhu, A.; Hu, J.; Pujara, J.; Ren, X.; Callison-Burch, C.; Choi, Y.; and Ammanabrolu, P.
In
Association for Computational Linguistics, pages 11136–11155, 2023.
link
bibtex
@inproceedings{zhou:acl23,
Author = "Zhou, Pei and Zhu, Andrew and Hu, Jennifer and Pujara, Jay and Ren, Xiang and Callison-Burch, Chris and Choi, Yejin and Ammanabrolu, Prithviraj",
acceptrate = "25\%",
bib_url = "/pubs/bib/zhou-acl23.bib",
booktitle = "Association for Computational Linguistics",
doi_url = "http://dx.doi.org/10.18653/v1/2023.acl-long.624",
pages = "11136--11155",
pdf_url = "/pubs/2023/zhou-acl23/zhou-acl23.pdf",
sec = "conf",
title = "{I} Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons",
year = "2023"
}
Identifying Informational Sources in News Articles.
Spangher, A.; Peng, N.; Ferrara, E.; and May, J.
In Bouamor, H.; Pino, J.; and Bali, K., editor(s),
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 3626–3639, Singapore, December 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
@inproceedings{spangher-etal-2023-identifying,
title = "Identifying Informational Sources in News Articles",
author = "Spangher, Alexander and
Peng, Nanyun and
Ferrara, Emilio and
May, Jonathan",
editor = "Bouamor, Houda and
Pino, Juan and
Bali, Kalika",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.emnlp-main.221",
doi = "10.18653/v1/2023.emnlp-main.221",
pages = "3626--3639",
abstract = "News articles are driven by the informational sources journalists use in reporting. Modeling when, how and why sources get used together in stories can help us better understand the information we consume and even help journalists with the task of producing it. In this work, we take steps toward this goal by constructing the largest and widest-ranging annotated dataset, to date, of informational sources used in news writing. We first show that our dataset can be used to train high-performing models for information detection and source attribution. Then, we introduce a novel task, source prediction, to study the compositionality of sources in news articles {--} i.e. how they are chosen to complement each other. We show good modeling performance on this task, indicating that there is a pattern to the way different sources are used \textit{together} in news storytelling. This insight opens the door for a focus on sources in narrative science (i.e. planning-based language generation) and computational journalism (i.e. a source-recommendation system to aid journalists writing stories). All data and model code can be found at https://github.com/alex2awesome/source-exploration.",
}
News articles are driven by the informational sources journalists use in reporting. Modeling when, how and why sources get used together in stories can help us better understand the information we consume and even help journalists with the task of producing it. In this work, we take steps toward this goal by constructing the largest and widest-ranging annotated dataset, to date, of informational sources used in news writing. We first show that our dataset can be used to train high-performing models for information detection and source attribution. Then, we introduce a novel task, source prediction, to study the compositionality of sources in news articles – i.e. how they are chosen to complement each other. We show good modeling performance on this task, indicating that there is a pattern to the way different sources are used together in news storytelling. This insight opens the door for a focus on sources in narrative science (i.e. planning-based language generation) and computational journalism (i.e. a source-recommendation system to aid journalists writing stories). All data and model code can be found at https://github.com/alex2awesome/source-exploration.
Identifying Quantifiably Verifiable Statements from Text.
Jandaghi, P.; and Pujara, J.
In
ACL Workshop on Matching From Unstructured and Structured Data , 2023.
link
bibtex
@inproceedings{jandaghi:acl23ws,
author = "Jandaghi, Pegah and Pujara, Jay",
bib_url = "/pubs/bib/jandaghi-acl23ws.bib",
doi_url = "https://doi.org/10.18653/v1/2023.matching-1.2",
pdf_url = "/pubs/2023/jandaghi-acl23ws/jandaghi-acl23ws.pdf",
title = "Identifying Quantifiably Verifiable Statements from Text",
booktitle = "ACL Workshop on Matching From Unstructured and Structured Data ",
sec = "ws",
year = "2023"
}
Identifying and Ranking Multiple Source Models for Transfer Learning in Unconventional Reservoirs.
Cornelio, J.; Mohd Razak, S.; Cho, Y.; Liu, H.; Vaidya, R.; and Jafarpour, B.
In
SPE Middle East Oil and Gas Show and Conference, pages D021S084R003, 2023. SPE
Paper
link
bibtex
@inproceedings{cornelio_identifying_2023,
title = {Identifying and {Ranking} {Multiple} {Source} {Models} for {Transfer} {Learning} in {Unconventional} {Reservoirs}.},
url = {https://onepetro.org/SPEMEOS/proceedings-abstract/23MEOS/2-23MEOS/517277},
urldate = {2024-02-12},
booktitle = {{SPE} {Middle} {East} {Oil} and {Gas} {Show} and {Conference}},
publisher = {SPE},
author = {Cornelio, Jodel and Mohd Razak, Syamil and Cho, Young and Liu, Hui-Hai and Vaidya, Ravimadhav and Jafarpour, Behnam},
year = {2023},
pages = {D021S084R003},
}
Identifying and characterizing behavioral classes of radicalization within the QAnon conspiracy on Twitter.
Wang, E. L; Luceri, L.; Pierri, F.; and Ferrara, E.
In
Proceedings of the 2023 International Conference of Web and Social Media (ICWSM), 2023.
link
bibtex
@inproceedings{wang2022identifying,
title={Identifying and characterizing behavioral classes of radicalization within the QAnon conspiracy on Twitter},
author={Wang, Emily L and Luceri, Luca and Pierri, Francesco and Ferrara, Emilio},
booktitle={Proceedings of the 2023 International Conference of Web and Social Media (ICWSM)},
year={2023}
}
Impact of Subword Pooling Strategy on Cross-lingual Event Detection.
Agarwal, S.; Fincke, S.; Jenkins, C.; Miller, S.; and Boschee, E.
CoRR, abs/2302.11365. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2302-11365,
author = {Shantanu Agarwal and
Steven Fincke and
Chris Jenkins and
Scott Miller and
Elizabeth Boschee},
title = {Impact of Subword Pooling Strategy on Cross-lingual Event Detection},
journal = {CoRR},
volume = {abs/2302.11365},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2302.11365},
doi = {10.48550/ARXIV.2302.11365},
eprinttype = {arXiv},
eprint = {2302.11365},
timestamp = {Tue, 28 Feb 2023 00:00:00 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2302-11365.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Improved Conflict-Based Search for the Virtual Network Embedding Problem.
Zheng, Y.; Ravi, S.; Kline, E.; Thurlow, L.; Koenig, S.; and Thittamaranahalli, S.
Proceedings of the Thirty-Second International Conference on Computer Communications and Networks (ICCCN-2023). 2023.
link
bibtex
@article{tksk05,
author={Yi Zheng and Srivatsan Ravi and Erik Kline and Lincoln Thurlow and Sven Koenig and Satish Thittamaranahalli},
title={Improved Conflict-Based Search for the Virtual Network Embedding Problem},
journal={Proceedings of the Thirty-Second International Conference on Computer Communications and Networks (ICCCN-2023)},
year={2023}
}
Improved Conflict-Based Search for the Virtual Network Embedding Problem.
Zheng, Y.; Ravi, S.; Kline, E.; Thurlow, L.; Koenig, S.; and Kumar, T. S.
In
2023 32nd International Conference on Computer Communications and Networks (ICCCN), pages 1–10, 2023. IEEE
link
bibtex
@inproceedings{zheng2023improved,
title={Improved Conflict-Based Search for the Virtual Network Embedding Problem},
author={Zheng, Yi and Ravi, Srivatsan and Kline, Erik and Thurlow, Lincoln and Koenig, Sven and Kumar, TK Satish},
booktitle={2023 32nd International Conference on Computer Communications and Networks (ICCCN)},
pages={1--10},
year={2023},
organization={IEEE}
}
In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision.
Datta, G.; Liu, Z.; Kaiser, M. A.; Kundu, S.; Mathai, J.; Yin, Z.; Jacob, A. P.; Jaiswal, A. R.; and Beerel, P. A.
In
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1-5, 2023.
doi
link
bibtex
@INPROCEEDINGS{10094902,
author={Datta, Gourav and Liu, Zeyu and Kaiser, Md Abdullah-Al and Kundu, Souvik and Mathai, Joe and Yin, Zihan and Jacob, Ajey P. and Jaiswal, Akhilesh R. and Beerel, Peter A.},
booktitle={ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision},
year={2023},
volume={},
number={},
pages={1-5},
keywords={Wireless communication;Energy consumption;Wireless sensor networks;Signal processing algorithms;Bandwidth;Signal processing;Data transfer},
doi={10.1109/ICASSP49357.2023.10094902}}
Indirect Cooperation in Distributed Stationary-Resource Searching with Predefined Destinations.
Lin, F.; and Knoblock, C. A.
In
Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems, of
SIGSPATIAL '23, New York, NY, USA, 2023. Association for Computing Machinery
Paper
doi
link
bibtex
abstract
@inproceedings{10.1145/3589132.3625571,
author = {Lin, Fandel and Knoblock, Craig A.},
title = {Indirect Cooperation in Distributed Stationary-Resource Searching with Predefined Destinations},
year = {2023},
isbn = {9798400701689},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3589132.3625571},
doi = {10.1145/3589132.3625571},
abstract = {Private vehicles are a direct means to bring people from one place to their desired destinations. However, no omniscient dispatcher is handling the origin-destination of vehicles and the availability of stationary resources, such as parking spaces or charging stations. Competitive cruising for stationary resources leads to environmental pollution and is a waste of drivers' time. We focus on the problem of distributed stationary-resource searching with predefined destinations under a multi-agent scenario. It is a distributed route planning problem with global optimization objectives. We present a probabilistic approach to achieving indirect resource coordination and latent agent cooperation in a distributed manner. Our approach treats the estimated availability of stationary resources as a reference and guides each agent based on their preferences. We evaluate our approach on four real-world datasets. Our approach outperforms state-of-the-art methods by 5\% in multi-criteria optimization.},
booktitle = {Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems},
articleno = {26},
numpages = {12},
keywords = {stationary-resource searching, distributed route planning, multi-criteria optimization},
location = {, Hamburg, Germany, },
series = {SIGSPATIAL '23}
}
Private vehicles are a direct means to bring people from one place to their desired destinations. However, no omniscient dispatcher is handling the origin-destination of vehicles and the availability of stationary resources, such as parking spaces or charging stations. Competitive cruising for stationary resources leads to environmental pollution and is a waste of drivers' time. We focus on the problem of distributed stationary-resource searching with predefined destinations under a multi-agent scenario. It is a distributed route planning problem with global optimization objectives. We present a probabilistic approach to achieving indirect resource coordination and latent agent cooperation in a distributed manner. Our approach treats the estimated availability of stationary resources as a reference and guides each agent based on their preferences. We evaluate our approach on four real-world datasets. Our approach outperforms state-of-the-art methods by 5% in multi-criteria optimization.
Inferring Changes in Daily Human Activity from Internet Response.
Song, X.; Baltra, G.; and Heidemann, J.
In
Proceedings of the ACM Internet Measurement Conference, pages to appear, Montreal, QC, Canada, October 2023. ACM
Paper
doi
link
bibtex
abstract
@InProceedings{Song23a,
author = "Xiao Song and Guillermo Baltra and John Heidemann",
title = "Inferring Changes in Daily Human Activity from Internet Response",
booktitle = "Proceedings of the " # "ACM Internet Measurement Conference",
year = 2023,
sortdate = "2023-10-26",
project = "ant, eieio, internetmap, minceq",
jsubject = "network_topology",
pages = "to appear",
month = oct,
address = "Montreal, QC, Canada",
publisher = "ACM",
jlocation = "johnh: pafile",
keywords = "internet, address scans, covid-19, poster, trinocular",
url = "https://ant.isi.edu/%7ejohnh/PAPERS/Song23a.html",
pdfurl = "https://ant.isi.edu/%7ejohnh/PAPERS/Song23a.pdf",
blogurl = "https://ant.isi.edu/blog/?p=1998",
dataseturl = "https://ant.isi.edu/datasets/ip_accumulation/",
doi = "https://doi.org/10.1145/3618257.3624796",
abstract = "Network traffic is often diurnal, with some networks peaking during
the workday and many homes during evening streaming hours. Monitoring
systems consider diurnal trends for capacity planning and anomaly
detection. In this paper, we reverse this inference and
use \emph{diurnal network trends and their absence to infer human activity}.
We draw on existing and new ICMP echo-request scans of
more than 5.2M /24 IPv4 networks to identify diurnal trends in IP
address responsiveness. Some of these networks
are \emph{change-sensitive}, with diurnal patterns correlating with human
activity. We develop algorithms to clean this data, extract
underlying trends from diurnal and weekly fluctuation, and detect
changes in that activity. Although firewalls hide many networks, and
Network Address Translation often hides human trends, we show about
168k to 330k (3.3--6.4\% of the 5.2M) /24 IPv4 networks are
change-sensitive. These blocks are spread globally, representing some
of the most active 60\% of \twotwodegree geographic gridcells, regions
that include 98.5\% of ping-responsive blocks. Finally, we detect
interesting changes in human activity. Reusing existing data allows
our new algorithm to identify changes, such as Work-from-Home due to
the global reaction to the emergence of Covid-19 in 2020. We also see
other changes in human activity, such as national holidays and
government-mandated curfews. This ability to detect trends in human
activity from the Internet data provides a new ability to understand
our world, complementing other sources of public information such as
news reports and wastewater virus observation.",
}
Network traffic is often diurnal, with some networks peaking during the workday and many homes during evening streaming hours. Monitoring systems consider diurnal trends for capacity planning and anomaly detection. In this paper, we reverse this inference and use \emphdiurnal network trends and their absence to infer human activity. We draw on existing and new ICMP echo-request scans of more than 5.2M /24 IPv4 networks to identify diurnal trends in IP address responsiveness. Some of these networks are \emphchange-sensitive, with diurnal patterns correlating with human activity. We develop algorithms to clean this data, extract underlying trends from diurnal and weekly fluctuation, and detect changes in that activity. Although firewalls hide many networks, and Network Address Translation often hides human trends, we show about 168k to 330k (3.3–6.4% of the 5.2M) /24 IPv4 networks are change-sensitive. These blocks are spread globally, representing some of the most active 60% of \twotwodegree geographic gridcells, regions that include 98.5% of ping-responsive blocks. Finally, we detect interesting changes in human activity. Reusing existing data allows our new algorithm to identify changes, such as Work-from-Home due to the global reaction to the emergence of Covid-19 in 2020. We also see other changes in human activity, such as national holidays and government-mandated curfews. This ability to detect trends in human activity from the Internet data provides a new ability to understand our world, complementing other sources of public information such as news reports and wastewater virus observation.
Is Dynamicity All You Need?.
Myloth, R. D.; Ahrabian, K.; Ananthan, A. B. S.; Du, X.; and Pujara, J.
In
Workshop on Scientific Document Understanding at AAAI, 2023.
link
bibtex
@inproceedings{myloth:aaai23ws,
Author = "Myloth, Richard Delwin and Ahrabian, Kian and Ananthan, Arun Baalaaji Sankar and Du, Xinwei and Pujara, Jay",
bib_url = "/pubs/bib/myloth-aaai23ws.bib",
booktitle = "Workshop on Scientific Document Understanding at AAAI",
pdf_url = "/pubs/2023/myloth-aaai23ws/myloth-aaai23ws.pdf",
sec = "ws",
title = "Is Dynamicity All You Need?",
year = "2023"
}
Knowledge Graph-based Embedding for Connecting Scholars in Academic Social Networks.
Cheng, X.; Zhang, Y.; Joshi, H.; Kejriwal, M.; and Calyam, P.
In
2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA), pages 1–10, 2023. IEEE
link
bibtex
@inproceedings{cheng2023knowledge,
title={Knowledge Graph-based Embedding for Connecting Scholars in Academic Social Networks},
author={Cheng, Xiyao and Zhang, Yuanxun and Joshi, Harsh and Kejriwal, Mayank and Calyam, Prasad},
booktitle={2023 IEEE 10th International Conference on Data Science and Advanced Analytics (DSAA)},
pages={1--10},
year={2023},
organization={IEEE}
}
LIMA: Less Is More for Alignment.
Zhou, C.; Liu, P.; Xu, P.; Iyer, S.; Sun, J.; Mao, Y.; Ma, X.; Efrat, A.; Yu, P.; YU, L.; Zhang, S.; Ghosh, G.; Lewis, M.; Zettlemoyer, L.; and Levy, O.
In
Thirty-seventh Conference on Neural Information Processing Systems, 2023.
link
bibtex
@inproceedings{zhou2023lima,
title={{LIMA}: Less Is More for Alignment},
author={Chunting Zhou and Pengfei Liu and Puxin Xu and Srini Iyer and Jiao Sun and Yuning Mao and Xuezhe Ma and Avia Efrat and Ping Yu and LILI YU and Susan Zhang and Gargi Ghosh and Mike Lewis and Luke Zettlemoyer and Omer Levy},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023}
}
Labeling without Seeing? Blind Annotation for Privacy-Preserving Entity Resolution.
Yao, Y.; Jin, W.; and Ravi, S.
CoRR, abs/2308.03734. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2308-03734,
author = {Yixiang Yao and
Weizhao Jin and
Srivatsan Ravi},
title = {Labeling without Seeing? Blind Annotation for Privacy-Preserving Entity
Resolution},
journal = {CoRR},
volume = {abs/2308.03734},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2308.03734},
doi = {10.48550/ARXIV.2308.03734},
eprinttype = {arXiv},
eprint = {2308.03734},
timestamp = {Tue, 22 Aug 2023 13:58:15 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2308-03734.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Leader: Defense Against Exploit-Based Denial-of-Service Attacks on Web Applications.
Tandon, R.; Wang, H.; Weideman, N.; Arakelyan, S.; Bartlett, G.; Hauser, C.; and Mirkovic, J.
In
Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses, pages 744–758, 2023.
link
bibtex
@inproceedings{tandon2023leader,
title={Leader: Defense Against Exploit-Based Denial-of-Service Attacks on Web Applications},
author={Tandon, Rajat and Wang, Haoda and Weideman, Nicolaas and Arakelyan, Shushan and Bartlett, Genevieve and Hauser, Christophe and Mirkovic, Jelena},
booktitle={Proceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses},
pages={744--758},
year={2023}
}
Learn Your Tokens: Word-Pooled Tokenization for Language Modeling.
Thawani, A.; Ghanekar, S.; Zhu, X.; and Pujara, J.
In
Findings of the Association for Computational Linguistics: EMNLP, 2023.
link
bibtex
@inproceedings{thawani:emnlpf23,
author = "Thawani, Avijit and Ghanekar, Saurabh and Zhu, Xiaoyuan and Pujara, Jay",
acceptrate = "46.2\%",
arxiv_url = "https://arxiv.org/pdf/2310.11628",
bib_url = "/pubs/bib/thawani-emnlpf23.bib",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP",
doi_url = "https://doi.org/10.18653/v1/2023.findings-emnlp.662",
pdf_url = "/pubs/2023/thawani-emnlpf23/thawani-emnlpf23.pdf",
sec = "conf",
title = "Learn Your Tokens: Word-Pooled Tokenization for Language Modeling",
year = "2023"
}
Lessons Learned: Building a Privacy-Preserving Entity Resolution Adaptation of PPJoin using End-to-End Homomorphic Encryption.
Ghai, T.; Yao, Y.; and Ravi, S.
In
IEEE European Symposium on Security and Privacy, EuroS&P 2023 - Workshops, Delft, Netherlands, July 3-7, 2023, pages 117–124, 2023. IEEE
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/eurosp/GhaiYR23,
author = {Tanmay Ghai and
Yixiang Yao and
Srivatsan Ravi},
title = {Lessons Learned: Building a Privacy-Preserving Entity Resolution Adaptation
of PPJoin using End-to-End Homomorphic Encryption},
booktitle = {{IEEE} European Symposium on Security and Privacy, EuroS{\&}P
2023 - Workshops, Delft, Netherlands, July 3-7, 2023},
pages = {117--124},
publisher = {{IEEE}},
year = {2023},
url = {https://doi.org/10.1109/EuroSPW59978.2023.00018},
doi = {10.1109/EUROSPW59978.2023.00018},
timestamp = {Mon, 07 Aug 2023 15:56:24 +0200},
biburl = {https://dblp.org/rec/conf/eurosp/GhaiYR23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Let's Put the Science in eScience.
Kesselman, C.; Schuler, R.; and Foster, I.
In
2023 IEEE 19th International Conference on E-Science (e-Science), pages 1–3, Limassol, Cyprus, October 2023. IEEE
doi
link
bibtex
@inproceedings{Kesselman2023,
address = {{Limassol, Cyprus}},
author = {Kesselman, Carl and Schuler, Robert and Foster, Ian},
booktitle = {2023 {{IEEE}} 19th {{International Conference}} on E-{{Science}} (e-{{Science}})},
date-added = {2024-01-22 12:05:54 -0800},
date-modified = {2024-01-22 12:05:54 -0800},
doi = {10.1109/e-Science58273.2023.10254914},
month = oct,
pages = {1--3},
publisher = {{IEEE}},
title = {Let's {{Put}} the {{Science}} in {{eScience}}},
year = {2023},
bdsk-url-1 = {https://doi.org/10.1109/e-Science58273.2023.10254914}}
Leveraging Label Correlations in a Multi-Label Setting: a Case Study in Emotion.
Chochlakis, G.; Mahajan, G.; Baruah, S.; Burghardt, K.; Lerman, K.; and Narayanan, S.
In
IEEE International Conference on Acoustics, Speech and Signal Processing ICASSP 2023, Rhodes Island, Greece, June 4-10, 2023, pages 1–5, 2023. IEEE
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/icassp/ChochlakisMBBLN23,
author = {Georgios Chochlakis and
Gireesh Mahajan and
Sabyasachee Baruah and
Keith Burghardt and
Kristina Lerman and
Shrikanth Narayanan},
title = {Leveraging Label Correlations in a Multi-Label Setting: a Case Study
in Emotion},
booktitle = {{IEEE} International Conference on Acoustics, Speech and Signal Processing
{ICASSP} 2023, Rhodes Island, Greece, June 4-10, 2023},
pages = {1--5},
publisher = {{IEEE}},
year = {2023},
url = {https://doi.org/10.1109/ICASSP49357.2023.10096864},
doi = {10.1109/ICASSP49357.2023.10096864},
timestamp = {Sun, 05 Nov 2023 16:51:21 +0100},
biburl = {https://dblp.org/rec/conf/icassp/ChochlakisMBBLN23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Look-back Decoding for Open-Ended Text Generation.
Xu, N.; Zhou, C.; Celikyilmaz, A.; and Ma, X.
In
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 1039–1050, Singapore, December 2023. Association for Computational Linguistics
link
bibtex
@inproceedings{xu-etal-2023-look,
title = "Look-back Decoding for Open-Ended Text Generation",
author = "Xu, Nan and Zhou, Chunting and Celikyilmaz, Asli and Ma, Xuezhe",
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
pages = "1039--1050",
}
Low-Resource Financial QA with Case-based Reasoning.
Sun, K.; and Pujara, J.
In
KDD Workshop on Robust NLP for Finance, 2023.
link
bibtex
@inproceedings{sun:kdd23ws,
Author = "Sun, Kexuan and Pujara, Jay",
bib_url = "/pubs/bib/sun-kdd23ws.bib",
booktitle = "KDD Workshop on Robust NLP for Finance",
pdf_url = "/pubs/2023/sun-kdd23ws/sun-kdd23ws.pdf",
sec = "ws",
title = "Low-Resource Financial QA with Case-based Reasoning",
year = "2023"
}
Making Large Language Models Better Data Creators.
Lee, D.; Pujara, J.; Sewak, M.; White, R.; and Jauhar, S.
In
Conference on Empirical Methods in Natural Language Processing, 2023.
link
bibtex
@inproceedings{lee:emnlp23b,
author = "Lee, Dong-Ho and Pujara, Jay and Sewak, Mohit and White, Ryen and Jauhar, Sujay",
acceptrate = "23.3\%",
arxiv_url = "https://arxiv.org/pdf/2310.20111",
bib_url = "/pubs/bib/lee-emnlp23b.bib",
booktitle = "Conference on Empirical Methods in Natural Language Processing",
code_url = "https://github.com/microsoft/llm-data-creation",
doi_url = "https://doi.org/10.18653/v1/2023.emnlp-main.948",
pdf_url = "/pubs/2023/lee-emnlp23b/lee-emnlp23b.pdf",
sec = "conf",
title = "Making Large Language Models Better Data Creators",
year = "2023"
}
21.
Orosz, M.
Managing Risk, pages 463-470. John Wiley & Sons, Ltd, 2023.
Paper
doi
link
bibtex
abstract
@inbook{doi:https://doi.org/10.1002/9781394203314.ch21,
author = {Orosz, Michael},
publisher = {John Wiley & Sons, Ltd},
isbn = {9781394203314},
title = {Managing Risk},
booktitle = {Systems Engineering for the Digital Age},
chapter = {21},
pages = {463-470},
doi = {https://doi.org/10.1002/9781394203314.ch21},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394203314.ch21},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781394203314.ch21},
year = {2023},
keywords = {risk, technical risk, system risk, obsolescence, risk management, agile risk management},
abstract = {Summary Risk is generally defined as the measure of the potential inability to achieve overall program objectives within defined cost, schedule, and technical constraints. What is missing from this definition are risks associated with failing to identify and capture evolving user, system, and technical requirements, which are often driven by evolving end-user or marketplace demands. Ignoring these evolving needs introduces risks, meaning you may be developing an obsolete product or one that only partially meets end-user needs. There are many different flavors of risk management, but each of these includes considerations for defining and assessing risk (including the likelihood it will occur and the potential impact if it does), determining how to decide which risks to mitigate and how to do so, and risk monitoring. This chapter focuses on managing three types of risks to systems engineering and development: project development risk, technical risk, and obsolescence risk.}
}
Summary Risk is generally defined as the measure of the potential inability to achieve overall program objectives within defined cost, schedule, and technical constraints. What is missing from this definition are risks associated with failing to identify and capture evolving user, system, and technical requirements, which are often driven by evolving end-user or marketplace demands. Ignoring these evolving needs introduces risks, meaning you may be developing an obsolete product or one that only partially meets end-user needs. There are many different flavors of risk management, but each of these includes considerations for defining and assessing risk (including the likelihood it will occur and the potential impact if it does), determining how to decide which risks to mitigate and how to do so, and risk monitoring. This chapter focuses on managing three types of risks to systems engineering and development: project development risk, technical risk, and obsolescence risk.
Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search.
Jenkins, C.; Agarwal, S.; Barry, J.; Fincke, S.; and Boschee, E.
CoRR, abs/2305.10561. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2305-10561,
author = {Chris Jenkins and
Shantanu Agarwal and
Joel Barry and
Steven Fincke and
Elizabeth Boschee},
title = {Massively Multi-Lingual Event Understanding: Extraction, Visualization,
and Search},
journal = {CoRR},
volume = {abs/2305.10561},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2305.10561},
doi = {10.48550/ARXIV.2305.10561},
eprinttype = {arXiv},
eprint = {2305.10561},
timestamp = {Thu, 25 May 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2305-10561.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Measuring Online Emotional Reactions to Offline Events.
Guo, S.; He, Z.; Rao, A.; Jang, E.; Nan, Y.; Morstatter, F.; Brantingham, P. J.; and Lerman, K.
CoRR, abs/2307.10245. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2307-10245,
author = {Siyi Guo and
Zihao He and
Ashwin Rao and
Eugene Jang and
Yuanfeixue Nan and
Fred Morstatter and
P. Jeffrey Brantingham and
Kristina Lerman},
title = {Measuring Online Emotional Reactions to Offline Events},
journal = {CoRR},
volume = {abs/2307.10245},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2307.10245},
doi = {10.48550/ARXIV.2307.10245},
eprinttype = {arXiv},
eprint = {2307.10245},
timestamp = {Wed, 26 Jul 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2307-10245.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Mega: moving average equipped gated attention.
Ma, X.; Zhou, C.; Kong, X.; He, J.; Gui, L.; Neubig, G.; May, J.; and Zettlemoyer, L.
In
Proceedings of the 11th International Conference on Learning Representations (ICLR-2023), 2023.
link
bibtex
@inproceedings{ma2023mega,
title={Mega: moving average equipped gated attention},
author={Ma, Xuezhe and Zhou, Chunting and Kong, Xiang and He, Junxian and Gui, Liangke and Neubig, Graham and May, Jonathan and Zettlemoyer, Luke},
booktitle={Proceedings of the 11th International Conference on Learning Representations (ICLR-2023)},
year={2023}
}
MetisFL: An Embarrassingly Parallelized Controller for Scalable & Efficient Federated Learning Workflows.
Stripelis, D.; Anastasiou, C.; Toral, P.; Asghar, A.; and Ambite, J. L.
In
Proceedings of the 4th International Workshop on Distributed Machine Learning, of
DistributedML '23, pages 11–19, New York, NY, USA, December 2023. Association for Computing Machinery
Paper
doi
link
bibtex
@inproceedings{stripelis2023:metisfl,
address = {New York, NY, USA},
series = {{DistributedML} '23},
title = {{MetisFL}: {An} {Embarrassingly} {Parallelized} {Controller} for {Scalable} \& {Efficient} {Federated} {Learning} {Workflows}},
isbn = {9798400704475},
shorttitle = {{MetisFL}},
url = {https://doi.org/10.1145/3630048.3630186},
doi = {10.1145/3630048.3630186},
urldate = {2024-01-27},
booktitle = {Proceedings of the 4th {International} {Workshop} on {Distributed} {Machine} {Learning}},
publisher = {Association for Computing Machinery},
author = {Stripelis, Dimitris and Anastasiou, Chrysovalantis and Toral, Patrick and Asghar, Armaghan and Ambite, Jos\'{e} Luis},
month = dec,
year = {2023},
keywords = {data management, distributed machine learning, federated learning, machine learning systems},
pages = {11--19},
}
Minimizing die fracture in three-dimensional IC advanced packaging wafer thinning process by inserting polyimide patterns.
?Jaime Bravo, P. M.; Lifu Chang, E. B.; and Frederic Brault, J. Z.
In
Proceedings of SPIE, 2023.
doi
link
bibtex
@inproceedings{spie2023minimizefracture,
title={Minimizing die fracture in three-dimensional IC advanced packaging wafer thinning process by inserting polyimide patterns},
author={?Jaime Bravo, Philippe Morey-Chaisemartin, Lifu Chang, Eric Beisser, Frederic Brault, Joshua Zusman},
booktitle={Proceedings of SPIE},
number={1249511},
doi={https://doi.org/10.1117/12.2657011},
year={2023}
}
Minimizing die fracture in three-dimensional IC advanced packaging wafer thinning process by inserting polyimide patterns.
Bravo, J.; Morey-Chaisemartin, P.; Chang, L.; Beisser, E.; Brault, F.; and Zusman, J.
In Kim, R.; and Lafferty, N. V., editor(s),
DTCO and Computational Patterning II, volume 12495, pages 1249511, 2023. International Society for Optics and Photonics, SPIE
Paper
doi
link
bibtex
@inproceedings{10.1117/12.2657011,
author = {Jaime Bravo and Philippe Morey-Chaisemartin and Lifu Chang and Eric Beisser and Frederic Brault and Joshua Zusman},
title = {{Minimizing die fracture in three-dimensional IC advanced packaging wafer thinning process by inserting polyimide patterns}},
volume = {12495},
booktitle = {DTCO and Computational Patterning II},
editor = {Ryoung-Han Kim and Neal V. Lafferty},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {1249511},
keywords = {Advanced Packaging, 3D ICs, 3D Integration, Frame Generation, Thin Wafer, Fracture, Stress, Patterning},
year = {2023},
doi = {10.1117/12.2657011},
URL = {https://doi.org/10.1117/12.2657011}
}
Modeling Cross-Cultural Pragmatic Inference with Codenames Duet.
Shaikh, O.; Ziems, C.; Held, W.; Pariani, A. J; Morstatter, F.; and Yang, D.
Association of Computational Linguistics. 2023.
link
bibtex
@article{shaikh2023modeling,
title={Modeling Cross-Cultural Pragmatic Inference with Codenames Duet},
author={Shaikh, Omar and Ziems, Caleb and Held, William and Pariani, Aryan J and Morstatter, Fred and Yang, Diyi},
journal={Association of Computational Linguistics},
year={2023}
}
Modeling cognitive workload in open-source communities via simulation.
Tregubov, A.; Abramson, J.; Hauser, C.; Hussain, A.; and Blythe, J.
In
AAMAS International Workshop on Multi-Agent-Based Simulation, 2023.
Paper
link
bibtex
@inproceedings{tregubov2023mabs,
title={Modeling cognitive workload in open-source communities via simulation},
author={Tregubov, Alexey and Abramson, Jeremy and Hauser, Christophe and Hussain, Alefiya and Blythe, Jim},
booktitle={AAMAS International Workshop on Multi-Agent-Based Simulation},
url = {https://mabsworkshop.github.io/mabs2023/mabs2023/articles/tregubovEtAl2023.pdf},
year={2023}
}
Multi-agent Game Domain: Monopoly.
Bonjour, T; Haliem, M; Aggarwal, V; Kejriwal, M; and Bhargava, B
In
A Unifying Framework for Formal Theories of Novelty: Discussions, Guidelines, and Examples for Artificial Intelligence, pages 97–105. Springer, 2023.
link
bibtex
@incollection{bonjour2023multi,
title={Multi-agent Game Domain: Monopoly},
author={Bonjour, T and Haliem, M and Aggarwal, V and Kejriwal, M and Bhargava, B},
booktitle={A Unifying Framework for Formal Theories of Novelty: Discussions, Guidelines, and Examples for Artificial Intelligence},
pages={97--105},
year={2023},
publisher={Springer}
}
NRE-013: The Global Network Advancement Group: A Next Generation System for Data Intensive Sciences.
Newman, H.; Balcas, J.; Sirvinskas, R.; Iordache, C.; Bhat, P.; Moya, A.; Uppalapati, S.; Chang, J.; Mughal, A.; Boyd, D.; Williams, D. S.; Wuerthwein, F.; deFanti , T.; Smarr, L.; Graham, J.; Hutton, T.; Mishin, D.; Guiang, J.; Davila, D.; Sfiligoi, I.; Arora, A.; Yang, R.; Yang, R.; Zhang, J.; Yeh, E.; Wu, Y.; Mutlu, V.; Liu, Y.; Shannigrahi, S.; Timilsina, S.; Zhang, L.; Cong, J.; Lo, M.; Song, S.; Gutsche, O.; Demar, P.; Monga, I.; Lehman, C. G. T.; MacAuley, J.; Yang, X.; Balcas, J.; Kiran, M.; Sim, A.; Attenbury, G.; Melo, A.; Martelli, E.; Misa, C.; Ros-Giralt, J.; Martinello, M.; Ribeiro, M. R.; Dominicini, C.; Borges, E.; Guimaraes, R.; Schwarz, M.; Ciuffo, L.; LOUI, F.; Novaes, S.; Iope, R.; Francisco, A. J F; Lemke, N.; Ruggiero, C. A.; de Almeida, J. M.; Baldim, B.; Simionato, P.; Santoro, A.; Revoredo, E.; Rigo, S.; Jabbari, B.; Sobieski, J.; Zhang, L.; Xiang, Q.; Huang, C.; Wen, R.; Wang, Y.; shu , J.; Fox, L.; Bruton, C.; Bellamine, S.; Nguyen, T.; Anderson, C.; Mambretti, J.; Chen, J.; Yeh, F.; Wilkinson, C.; Zekauskas, M.; Todorov, C.; Ibarra, J.; Bezerra, J.; Chergarova, V.; Ulloa, A.; Morgan, H.; Kohlert, S.; Lyonnais, M.; Wilson, R.; Cho, B.; Hussain, M.; Park, C.; Tam, T.; Moura, A.; Sale, K.; Roos, J.; Hoeft, B.; Lee, C.; Pasavento, D.; Zane, C.; Trompert, H.; Hažlinský, M.; McKnight, C.; Ku, L.; Perrig, A.; Kwon, J.; Wirz, F.; Hausheer, D.; Gartner, M.; Pillay, K.; Johnston, B.; Hugo, J.; Diamini, S.; Greaves, D.; Sullivan, P.; Makan, A.; Hay, J.; van Heerden, R. P.; Khwela, T.; Wilde, D.; and Members, G. A. / S. W.
11/2023 2023.
Paper
link
bibtex
@conference{newman2023a,
author = {Harvey Newman and Justas Balcas and Raimondas Sirvinskas and Catalin Iordache and Preeti Bhat and Andres Moya and Sravya Uppalapati and Jin Chang and Azher Mughal and Dawn Boyd and Don S. Williams and Frank Wuerthwein and Tom deFanti and Larry Smarr and John Graham and Tom Hutton and Dima Mishin and Jonathan Guiang and Diego Davila and Igor Sfiligoi and Aashay Arora and Richard Yang and Ryan Yang and Jensen Zhang and Edmund Yeh and Yuanhao Wu and Volkan Mutlu and Yuezhou Liu and Susmit Shannigrahi and Sankalpa Timilsina and Lixia Zhang and Jason Cong and Michael Lo and Sichen Song and Oliver Gutsche and Phil Demar and Inder Monga and Chin Guok Tom Lehman and John MacAuley and Xi Yang and Justas Balcas and Mariam Kiran and Alex Sim and Garhan Attenbury and Andrew Melo and Edoardo Martelli and Carmen Misa and Jordi Ros-Giralt and Magnos Martinello and Moises R.N. Ribeiro and Christina Dominicini and Everson Borges and Rafael Guimaraes and Marcos Schwarz and Leandro Ciuffo and Frédéric LOUI and Sergio Novaes and Rogerio Iope and Antonio J F Francisco and Ney Lemke and Carlos Antonio Ruggiero and Jorge Marcos de Almeida and Bruno Baldim and Paulo Simionato and Alberto Santoro and Eduardo Revoredo and Sandro Rigo and Bijan Jabbari and Jerry Sobieski and Liang Zhang and Qiao Xiang and Chenyang Huang and Ridi Wen and Yuxin Wang and Jiwu shu and Louis Fox and Christopher Bruton and Sana Bellamine and Tony Nguyen and Celeste Anderson and Joe Mambretti and Jim Chen and Fei Yeh and Chris Wilkinson and Matt Zekauskas and Christian Todorov and Julio Ibarra and Jeronimo Bezerra and Vasilka Chergarova and Anthony Ulloa and Heidi Morgan and Scott Kohlert and Marc Lyonnais and Rod Wilson and Buseung Cho and Mazahir Hussain and Changjin Park and Thomas Tam and Alex Moura and Kevin Sale and Jason Roos and Bruno Hoeft and Carlyn-Ann Lee and Davide Pasavento and Chris Zane and Hans Trompert and Michal Hažlinský and Cole McKnight and Li-Chi Ku and Adrian Perrig and Jonghoon Kwon and François Wirz and David Hausheer and Marten Gartner and Kasandra Pillay and Brian Johnston and Johann Hugo and Sibelo Diamini and Duncan Greaves and Paul Sullivan and Ajay Makan and John Hay and Renier Pelser van Heerden and Thokozani Khwela and David Wilde and GNA-G AutoGOLE / SENSE WG Members},
title = {NRE-013: The Global Network Advancement Group: A Next Generation System for Data Intensive Sciences},
journal = {Supercomputing Conference (SC23)},
year = {2023},
month = {11/2023},
pages = {Demonstration},
publisher = {Supercomputing Conference 2023 (SC23)},
type = {Conference Proceedings},
address = {Denver, CO},
url = {https://sc23.supercomputing.org/wp-content/uploads/2023/11/SC23-NRE-013-HarveyNewman-GNAGNextGenerationSystemforDataIntensiveSciences-1.pdf},
editor = {Experience}
}
NRE-013: Turbocharging 100G Link: A High-Speed Data Filling Demo from South Africa to Denver!.
Newman, H.; Ibarra, J.; Pillay, K.; Khwela, T.; van Heerden, R. P.; Greaves, D.; Makan, A.; Sullivan, P.; Johnston, B.; Schwarz, M. F.; Dlamini, S.; Hugo, J.; Hay, J.; Bezerra, J.; Ulloa, A.; Morgan, H.; and Chergarova, V.
11/2023 2023.
Paper
link
bibtex
@conference{newman2023,
author = {Harvey Newman and Julio Ibarra and Kasandra Pillay and Thokozani Khwela and Renier Pelser van Heerden and Duncan Greaves and Ajay Makan and Paul Sullivan and Bryan Johnston and Marcos Felipe Schwarz and Sabelo Dlamini and Johann Hugo and John Hay and Jeronimo Bezerra and Anthony Ulloa and Heidi Morgan and Vasilka Chergarova},
title = {NRE-013: Turbocharging 100G Link: A High-Speed Data Filling Demo from South Africa to Denver!},
journal = {Supercomputing Conference (SC23)},
year = {2023},
month = {11/2023},
pages = {Demonstration},
publisher = {Supercomputing Conference 2023 (SC23)},
type = {Conference Proceedings},
address = {Denver, CO},
url = {https://sc23.supercomputing.org/wp-content/uploads/2023/11/SC23-NRE-013-HarveyNewman-GNAGNextGenerationSystemforDataIntensiveSciences-1.pdf},
editor = {Experience}
}
NRE-019: AmLight 2.0: Flexible Control, Deep Visibility, and Programmability @ Tbps!.
Bezerra, J.; Brito, I. V. D. S.; Arcanjo, V.; Ibarra, J.; Frez, R.; Motitsuki, R.; Morgan, H.; Chergarova, V.; Baldim, B.; Bernardes, M. C.; Ferreira, J. E.; and Newman, H.
11/2023 2023.
Paper
link
bibtex
@conference{bezerra2023,
author = {Jeronimo Bezerra and Italo Valcy Da Silva Brito and Vinicius Arcanjo and Julio Ibarra and Renata Frez and Rogerio Motitsuki and Heidi Morgan and Vasilka Chergarova and Bruno Baldim and Mauro Cesar Bernardes and Joao Eduardo Ferreira and Harvey Newman},
title = {NRE-019: AmLight 2.0: Flexible Control, Deep Visibility, and Programmability @ Tbps!},
journal = {Supercomputing Conference (SC23)},
year = {2023},
month = {11/2023},
pages = {Demonstration},
publisher = {Supercomputing Conference 2023 (SC23)},
type = {Conference Proceedings},
address = {Denver, CO},
url = {https://sc23.supercomputing.org/wp-content/uploads/2023/11/SC23-NRE-019-JeronimoBezarra-AmLight_2.0_Flexible_control_deep_visibility_and_programmability_at_Tbps.pdf}
}
Network Services Management using Programmable Data Planes for Visual Cloud Computing.
Esquivel Morel, A.; Calyam, P.; Qu, C.; Gafurov, D.; Wang, C.; Thareja, K.; Mandal, A.; Lyons, E.; Zink, M.; Papadimitriou, G.; and Deelman, E.
In
2023 International Conference on Computing, Networking and Communications (ICNC), pages 130-136, 2023.
Funding Acknowledgments: NSF 1950873, 2018074
doi
link
bibtex
@InProceedings{ esquivel-morel-icnc-2023,
Author = {Esquivel Morel, Alicia and Calyam, Prasad and Qu, Chengyi
and Gafurov, Durbek and Wang, Cong and Thareja, Komal and
Mandal, Anirban and Lyons, Eric and Zink, Michael and
Papadimitriou, George and Deelman, Ewa},
BookTitle = {2023 International Conference on Computing, Networking and
Communications (ICNC)},
Title = {Network Services Management using Programmable Data Planes
for Visual Cloud Computing},
Year = {2023},
Volume = {},
ISSN = {},
Pages = {130-136},
DOI = {10.1109/ICNC57223.2023.10074183},
Note = {Funding Acknowledgments: NSF 1950873, 2018074}
}
Neural Network-Assisted Clustering for Improved Production Predictions in Unconventional Reservoirs.
Cornelio, J.; Mohd Razak, S.; Cho, Y.; Liu, H.; Vaidya, R.; and Jafarpour, B.
In
SPE Western Regional Meeting, pages D021S004R001, 2023. SPE
Paper
link
bibtex
@inproceedings{cornelio_neural_2023,
title = {Neural {Network}-{Assisted} {Clustering} for {Improved} {Production} {Predictions} in {Unconventional} {Reservoirs}},
url = {https://onepetro.org/SPEWRM/proceedings-abstract/23WRM/2-23WRM/519672},
urldate = {2024-02-12},
booktitle = {{SPE} {Western} {Regional} {Meeting}},
publisher = {SPE},
author = {Cornelio, Jodel and Mohd Razak, Syamil and Cho, Young and Liu, Hui-Hai and Vaidya, Ravimadhav and Jafarpour, Behnam},
year = {2023},
pages = {D021S004R001},
}
Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors.
Kaiser, M. A.; Datta, G.; Wang, Z.; Jacob, A. P.; Beerel, P. A.; and Jaiswal, A. R.
Frontiers in Neuroinformatics, 17. 2023.
Paper
doi
link
bibtex
abstract
@ARTICLE{10.3389/fninf.2023.1144301,
AUTHOR={Kaiser, Md Abdullah-Al and Datta, Gourav and Wang, Zixu and Jacob, Ajey P. and Beerel, Peter A. and Jaiswal, Akhilesh R.},
TITLE={Neuromorphic-P2M: processing-in-pixel-in-memory paradigm for neuromorphic image sensors},
JOURNAL={Frontiers in Neuroinformatics},
VOLUME={17},
YEAR={2023},
URL={https://www.frontiersin.org/articles/10.3389/fninf.2023.1144301},
DOI={10.3389/fninf.2023.1144301},
ISSN={1662-5196},
ABSTRACT={Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-efficient solutions such as near-sensor, in-sensor, and in-pixel processing, bringing the computation closer to the sensor. In particular, in-pixel processing embeds the computation capabilities inside the pixel array and achieves high energy efficiency by generating low-level features instead of the raw data stream from CMOS image sensors. Many different in-pixel processing techniques and approaches have been demonstrated on conventional frame-based CMOS imagers; however, the processing-in-pixel approach for neuromorphic vision sensors has not been explored so far. In this work, for the first time, we propose an asynchronous non-von-Neumann analog processing-in-pixel paradigm to perform convolution operations by integrating in-situ multi-bit multi-channel convolution inside the pixel array performing analog multiply and accumulate (MAC) operations that consume significantly less energy than their digital MAC alternative. To make this approach viable, we incorporate the circuit's non-ideality, leakage, and process variations into a novel hardware-algorithm co-design framework that leverages extensive HSpice simulations of our proposed circuit using the GF22nm FD-SOI technology node. We verified our framework on state-of-the-art neuromorphic vision sensor datasets and show that our solution consumes ~2× lower backend-processor energy while maintaining almost similar front-end (sensor) energy on the IBM DVS128-Gesture dataset than the state-of-the-art while maintaining a high test accuracy of 88.36%.}
}
Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources. Hence, researchers have been exploring different energy-efficient solutions such as near-sensor, in-sensor, and in-pixel processing, bringing the computation closer to the sensor. In particular, in-pixel processing embeds the computation capabilities inside the pixel array and achieves high energy efficiency by generating low-level features instead of the raw data stream from CMOS image sensors. Many different in-pixel processing techniques and approaches have been demonstrated on conventional frame-based CMOS imagers; however, the processing-in-pixel approach for neuromorphic vision sensors has not been explored so far. In this work, for the first time, we propose an asynchronous non-von-Neumann analog processing-in-pixel paradigm to perform convolution operations by integrating in-situ multi-bit multi-channel convolution inside the pixel array performing analog multiply and accumulate (MAC) operations that consume significantly less energy than their digital MAC alternative. To make this approach viable, we incorporate the circuit's non-ideality, leakage, and process variations into a novel hardware-algorithm co-design framework that leverages extensive HSpice simulations of our proposed circuit using the GF22nm FD-SOI technology node. We verified our framework on state-of-the-art neuromorphic vision sensor datasets and show that our solution consumes 2× lower backend-processor energy while maintaining almost similar front-end (sensor) energy on the IBM DVS128-Gesture dataset than the state-of-the-art while maintaining a high test accuracy of 88.36%.
Non-Binary Gender Expression in Online Interactions.
Dorn, R.; Jiang, J.; Abramson, J.; and Lerman, K.
CoRR, abs/2303.04837. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2303-04837,
author = {Rebecca Dorn and
Julie Jiang and
Jeremy Abramson and
Kristina Lerman},
title = {Non-Binary Gender Expression in Online Interactions},
journal = {CoRR},
volume = {abs/2303.04837},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2303.04837},
doi = {10.48550/ARXIV.2303.04837},
eprinttype = {arXiv},
eprint = {2303.04837},
timestamp = {Tue, 07 May 2024 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2303-04837.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Non-Binary Gender Expression in Online Interactions.
Dorn, R.; Negar, M.; Jiang, J.; Abramson, J.; Morstatter, F.; and Lerman, K.
In
"16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation", September 2023.
link
bibtex
@inproceedings{10.1007/978-3-031-43129-6_3,
title = {Non-Binary Gender Expression in Online Interactions},
author = {Dorn, Rebecca and Mokhberian Negar and Jiang, Julie and Abramson, Jeremy and Morstatter, Fred and Lerman, Kristina},
year = 2023,
month = {September},
booktitle = {"16th International Conference on Social Computing, Behavioral-Cultural Modeling & Prediction and Behavior Representation in Modeling and Simulation"},
doi = {}
}
Noncommuting conserved charges in quantum thermodynamics and beyond.
Majidy, S.; Braasch, W. F.; Lasek, A.; Upadhyaya, T.; Kalev, A.; and Yunger Halpern, N.
Nature Reviews Physics. Oct 2023.
Paper
doi
link
bibtex
@Article{Majidy2023,
author={Majidy, Shayan
and Braasch, William F.
and Lasek, Aleksander
and Upadhyaya, Twesh
and Kalev, Amir
and Yunger Halpern, Nicole},
title={Noncommuting conserved charges in quantum thermodynamics and beyond},
journal={Nature Reviews Physics},
year={2023},
month={Oct},
day={02},
issn={2522-5820},
doi={10.1038/s42254-023-00641-9},
url={https://doi.org/10.1038/s42254-023-00641-9}
}
Online Boosted Gaussian Learners for In-Situ Detection and Characterization of Protein Folding States in Molecular Dynamics Simulations.
Sahni, H.; Carrillo-Cabada, H.; Kots, E.; Caino-Lores, S.; Marquez, J.; Deelman, E.; Cuendet, M.; Weinstein, H.; Taufer, M.; and Estrada, T.
In
2023 IEEE 19th International Conference on e-Science (e-Science), pages 1-10, 2023.
Funding Acknowledgments: NSF 1757207, 1741057, 1841758, 2138811 and 2223704
doi
link
bibtex
@InProceedings{ sahni-esciences-2023,
Author = {Sahni, Harshita and Carrillo-Cabada, Hector and Kots,
Ekaterina and Caino-Lores, Silvina and Marquez, Jack and
Deelman, Ewa and Cuendet, Michel and Weinstein, Harel and
Taufer, Michela and Estrada, Trilce},
BookTitle = {2023 IEEE 19th International Conference on e-Science
(e-Science)},
Title = {Online Boosted Gaussian Learners for In-Situ Detection and
Characterization of Protein Folding States in Molecular
Dynamics Simulations},
Year = {2023},
Volume = {},
Number = {},
Pages = {1-10},
DOI = {10.1109/e-Science58273.2023.10254895},
Note = {Funding Acknowledgments: NSF 1757207, 1741057, 1841758,
2138811 and 2223704}
}
Online Networks of Support in Distressed Environments: Solidarity and Mobilization during the Russian Invasion of Ukraine.
Ye, J.; Jindal, N.; Pierri, F.; and Luceri, L.
In
AAAI ICWSM Workshop, 2023.
link
bibtex
@inproceedings{ye2023online,
title={Online Networks of Support in Distressed Environments: Solidarity and Mobilization during the Russian Invasion of Ukraine},
author={Ye, Jinyi and Jindal, Nikhil and Pierri, Francesco and Luceri, Luca},
booktitle={AAAI ICWSM Workshop},
year={2023}
}
Online search is more likely to lead students to validate true news than to refute false ones.
Bouleimen, A.; Luceri, L.; Cardoso, F.; Botturi, L.; Hermida, M.; Addimando, L.; Beretta, C.; Galloni, M.; and Giordano, S.
arXiv Preprint: https://arxiv.org/abs/2303.13138, 2023.
link
bibtex
@misc{bouleimen2023online,
title={Online search is more likely to lead students to validate true news than to refute false ones},
author={Bouleimen, Azza and Luceri, Luca and Cardoso, Felipe and Botturi, Luca and Hermida, Martin and Addimando, Loredana and Beretta, Chiara and Galloni, Marzia and Giordano, Silvia},
Eprint = {arXiv:2303.13138},
Howpublished = {arXiv Preprint: https://arxiv.org/abs/2303.13138},
year={2023}
}
Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distribution.
Rostami, M.; and Galstyan, A.
In
AAAI, 2023.
link
bibtex
@inproceedings{stan2022domain,
title={Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distribution},
author={Rostami, Mohammad and Galstyan, Aram},
booktitle={AAAI},
year={2023}
}
PINTO: Faithful Language Reasoning Using Prompted-Generated Rationales.
Wang, P.; Chan, A.; Ilievski, F.; Chen, M.; and Ren, X.
In
International Conference on Learning Representations, 2023.
link
bibtex
@inproceedings{wang2023pinto,
title={PINTO: Faithful Language Reasoning Using Prompted-Generated Rationales},
author={Wang, Peifeng and Chan, Aaron and Ilievski, Filip and Chen, Muhao and Ren, Xiang},
booktitle={International Conference on Learning Representations},
year={2023}
}
Pandemic Culture Wars: Partisan Asymmetries in the Moral Language of COVID-19 Discussions.
Rao, A.; Guo, S.; Wang, S. N.; Morstatter, F.; and Lerman, K.
CoRR, abs/2305.18533. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2305-18533,
author = {Ashwin Rao and
Siyi Guo and
Sze{-}Yuh Nina Wang and
Fred Morstatter and
Kristina Lerman},
title = {Pandemic Culture Wars: Partisan Asymmetries in the Moral Language
of {COVID-19} Discussions},
journal = {CoRR},
volume = {abs/2305.18533},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2305.18533},
doi = {10.48550/ARXIV.2305.18533},
eprinttype = {arXiv},
eprint = {2305.18533},
timestamp = {Wed, 07 Jun 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2305-18533.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Pandemic Culture Wars: Partisan Differences in the Moral Language of COVID-19 Discussions.
Rao, A.; Guo, S.; Wang, S. N.; Morstatter, F.; and Lerman, K.
In He, J.; Palpanas, T.; Hu, X.; Cuzzocrea, A.; Dou, D.; Slezak, D.; Wang, W.; Gruca, A.; Lin, J. C.; and Agrawal, R., editor(s),
IEEE International Conference on Big Data, BigData 2023, Sorrento, Italy, December 15-18, 2023, pages 413–422, 2023. IEEE
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/bigdataconf/RaoGWML23,
author = {Ashwin Rao and
Siyi Guo and
Sze{-}Yuh Nina Wang and
Fred Morstatter and
Kristina Lerman},
editor = {Jingrui He and
Themis Palpanas and
Xiaohua Hu and
Alfredo Cuzzocrea and
Dejing Dou and
Dominik Slezak and
Wei Wang and
Aleksandra Gruca and
Jerry Chun{-}Wei Lin and
Rakesh Agrawal},
title = {Pandemic Culture Wars: Partisan Differences in the Moral Language
of {COVID-19} Discussions},
booktitle = {{IEEE} International Conference on Big Data, BigData 2023, Sorrento,
Italy, December 15-18, 2023},
pages = {413--422},
publisher = {{IEEE}},
year = {2023},
url = {https://doi.org/10.1109/BigData59044.2023.10386084},
doi = {10.1109/BIGDATA59044.2023.10386084},
timestamp = {Fri, 02 Feb 2024 12:00:39 +0100},
biburl = {https://dblp.org/rec/conf/bigdataconf/RaoGWML23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Parameter-Efficient Tuning with Special Token Adaptation.
Yang, X.; Huang, J. Y; Zhou, W.; and Chen, M.
In
The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2023.
link
bibtex
@inproceedings{yang2023parameter,
title={Parameter-Efficient Tuning with Special Token Adaptation},
author={Yang, Xiaoocong and Huang, James Y and Zhou, Wenxuan and Chen, Muhao},
booktitle={The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL)},
year={2023}
}
Photonic-integrated circuit fabrication and test approaches.
Jacob, A. P.; Chandran, S.; Van Campenhout, J.; Pantouvaki, M.; Heck, J.; Giewont, K.; Rakowski, M.; Bian, Y.; Debackere, P.; and Kuntz, M.
In Glick, M.; Liao, L.; and Schmidtke, K., editor(s),
Integrated Photonics for Data Communication Applications, of Integrated Photonics Apps Specific Design &Manufacturing, pages 369-410. Elsevier, 2023.
Paper
doi
link
bibtex
abstract
@incollection{JACOB2023369,
title = {Photonic-integrated circuit fabrication and test approaches},
editor = {Madeleine Glick and Ling Liao and Katharine Schmidtke},
booktitle = {Integrated Photonics for Data Communication Applications},
publisher = {Elsevier},
pages = {369-410},
year = {2023},
series = {Integrated Photonics Apps Specific Design &Manufacturing},
isbn = {978-0-323-91224-2},
doi = {https://doi.org/10.1016/B978-0-323-91224-2.00012-6},
url = {https://www.sciencedirect.com/science/article/pii/B9780323912242000126},
author = {Ajey P. Jacob and Sujith Chandran and Joris {Van Campenhout} and Marianna Pantouvaki and John Heck and Ken Giewont and Michal Rakowski and Yusheng Bian and Peter Debackere and Matthias Kuntz},
keywords = {Photonic-integrated circuit, high-volume manufacturing, monolithic photonic-integrated circuit, heterogeneous photonic-integrated circuit, hybrid photonic-integrated circuit, fully photonic-integrated circuit, InP III–V photonic-integrated circuit, photonics in-line and end-of-line testing},
abstract = {Photonic-integrated circuits (PICs) integrate photonics elements, such as light sources, passive and active components, along with electronics elements, such as drivers, amplifiers, and application-specific integrated circuits, on a homogeneous or a heterogeneous material platform for various applications, such as data centers, communications, LIDAR, sensors, and spectroscopy. These components are fabricated separately or assembled monolithically on the silicon line to form the PIC. This chapter discusses the various chip fabrication and testing schemes leading to high-volume manufacturing of the PIC, such as (1) hybrid, (2) heterogeneous, (3) monolithic, (4) fully monolithic on silicon, and (5) indium phosphide III–V material platforms.}
}
Photonic-integrated circuits (PICs) integrate photonics elements, such as light sources, passive and active components, along with electronics elements, such as drivers, amplifiers, and application-specific integrated circuits, on a homogeneous or a heterogeneous material platform for various applications, such as data centers, communications, LIDAR, sensors, and spectroscopy. These components are fabricated separately or assembled monolithically on the silicon line to form the PIC. This chapter discusses the various chip fabrication and testing schemes leading to high-volume manufacturing of the PIC, such as (1) hybrid, (2) heterogeneous, (3) monolithic, (4) fully monolithic on silicon, and (5) indium phosphide III–V material platforms.
Physics-Guided Deep Learning for Improved Production Forecasting in Unconventional Reservoirs.
Mohd Razak, S.; Cornelio, J.; Cho, Y.; Liu, H.; Vaidya, R.; and Jafarpour, B.
SPE Journal,1–23. 2023.
Paper
link
bibtex
@article{mohd_razak_physics-guided_2023,
title = {Physics-{Guided} {Deep} {Learning} for {Improved} {Production} {Forecasting} in {Unconventional} {Reservoirs}},
url = {https://onepetro.org/SJ/article/doi/10.2118/214663-PA/519934},
urldate = {2024-02-12},
journal = {SPE Journal},
author = {Mohd Razak, Syamil and Cornelio, Jodel and Cho, Young and Liu, Hui-Hai and Vaidya, Ravimadhav and Jafarpour, Behnam},
year = {2023},
pages = {1--23},
}
Poor attention: The wealth and regional gaps in event attention and coverage on Wikipedia.
Ruprechter, T. A. B.; and Keith AND Helic, D.
PLOS ONE, 18(11): 1-19. 11 2023.
Paper
doi
link
bibtex
abstract
@article{Ruprechter2023_wiki,
abstract = {Wikipedia is an important source of general knowledge covering a wide range of topics. Moreover, for many people around the world, it also serves as an essential news source for major events such as elections or disasters. Although Wikipedia covers many such events, some events are underrepresented and lack attention, despite their newsworthiness predicted from news value theory. In this paper, we analyze 17 490 event articles in four Wikipedia language editions and examine how the economic status and geographic region of the event location affects the attention and coverage it receives. We find that major Wikipedia language editions have a skewed focus, with more attention given to events in the world's more economically developed countries and less attention to events in less affluent regions. However, other factors, such as the number of deaths in a disaster, are also associated with the attention an event receives. Overall, this work provides a nuanced understanding of attention and coverage on Wikipedia through event articles and adds new empirical analysis to news value theory.},
author = {Ruprechter, Thorsten AND Burghardt, Keith AND Helic, Denis},
doi = {10.1371/journal.pone.0289325},
journal = {PLOS ONE},
month = {11},
number = {11},
pages = {1-19},
publisher = {Public Library of Science},
title = {Poor attention: The wealth and regional gaps in event attention and coverage on Wikipedia},
url = {https://doi.org/10.1371/journal.pone.0289325},
volume = {18},
year = {2023},
bdsk-url-1 = {https://doi.org/10.1371/journal.pone.0289325}}
Wikipedia is an important source of general knowledge covering a wide range of topics. Moreover, for many people around the world, it also serves as an essential news source for major events such as elections or disasters. Although Wikipedia covers many such events, some events are underrepresented and lack attention, despite their newsworthiness predicted from news value theory. In this paper, we analyze 17 490 event articles in four Wikipedia language editions and examine how the economic status and geographic region of the event location affects the attention and coverage it receives. We find that major Wikipedia language editions have a skewed focus, with more attention given to events in the world's more economically developed countries and less attention to events in less affluent regions. However, other factors, such as the number of deaths in a disaster, are also associated with the attention an event receives. Overall, this work provides a nuanced understanding of attention and coverage on Wikipedia through event articles and adds new empirical analysis to news value theory.
Practical Intent-driven Routing Configuration Synthesis.
Ramanathan, S.; Zhang, Y.; Gawish, M.; Mundada, Y.; Wang, Z.; Yun, S.; Lippert, E.; Taha, W.; Yu, M.; and Mirkovic, J.
In
20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23), pages 629–644, 2023.
link
bibtex
@inproceedings{ramanathan2023practical,
title={Practical Intent-driven Routing Configuration Synthesis},
author={Ramanathan, Sivaramakrishnan and Zhang, Ying and Gawish, Mohab and Mundada, Yogesh and Wang, Zhaodong and Yun, Sangki and Lippert, Eric and Taha, Walid and Yu, Minlan and Mirkovic, Jelena},
booktitle={20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)},
pages={629--644},
year={2023}
}
Preface for the Second International Workshop on Knowledge Graph Generation from Text.
; and others
In
CEUR WORKSHOP PROCEEDINGS, volume 3447, pages 1–3, 2023. CEUR-WS
link
bibtex
@inproceedings{tiwari2023preface,
title={Preface for the Second International Workshop on Knowledge Graph Generation from Text},
author={ and others},
booktitle={CEUR WORKSHOP PROCEEDINGS},
volume={3447},
pages={1--3},
year={2023},
organization={CEUR-WS}
}
Priority-Based Search for the Virtual Network Embedding Problem.
Zheng, Y.; Ma, H.; Koenig, S.; Kline, E.; and Thittamaranahalli, S.
Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS-2023). 2023.
link
bibtex
@article{tksk02,
author={Yi Zheng and Hang Ma and Sven Koenig and Erik Kline and Satish Thittamaranahalli},
title={Priority-Based Search for the Virtual Network Embedding Problem},
journal={Proceedings of the Thirty-Third International Conference on Automated Planning and Scheduling (ICAPS-2023)},
year={2023}
}
Priority-Based Search for the Virtual Network Embedding Problem.
Zheng, Y.; Ma, H.; Koenig, S.; Kline, E.; and Kumar, T. K. S.
Proceedings of the International Conference on Automated Planning and Scheduling, 33(1): 472-480. Jul. 2023.
Paper
doi
link
bibtex
@article{Zheng_Ma_Koenig_Kline_Kumar_2023,
title={Priority-Based Search for the Virtual Network Embedding Problem},
volume={33}, url={https://ojs.aaai.org/index.php/ICAPS/article/view/27227},
DOI={10.1609/icaps.v33i1.27227},
number={1},
journal={Proceedings of the International Conference on Automated Planning and Scheduling},
author={Zheng, Yi and Ma, Hang and Koenig, Sven and Kline, Erik and Kumar, T. K. Satish},
year={2023},
month={Jul.},
pages={472-480}
}
PubGraph: A Large Scale Scientific Temporal Knowledge Graph.
Ahrabian, K.; Du, X.; Myloth, R. D.; Ananthan, A. B. S.; and Pujara, J.
2023.
Paper
link
bibtex
@unpublished{ahrabian:arxiv23,
author = "Ahrabian, Kian and Du, Xinwei and Myloth, Richard Delwin and Ananthan, Arun Baalaaji Sankar and Pujara, Jay",
sec = "preprint",
title = "PubGraph: A Large Scale Scientific Temporal Knowledge Graph",
url = "https://arxiv.org/pdf/2302.02231",
year = "2023"
}
QuantPipe: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments.
Wang, H.; Imes, C.; Kundu, S.; Beerel, P. A.; Crago, S. P.; and Paul Walters, J.
In
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pages 1-5, 2023.
doi
link
bibtex
@INPROCEEDINGS{QuantPipe,
author={Wang, Haonan and Imes, Connor and Kundu, Souvik and Beerel, Peter A. and Crago, Stephen P. and Paul Walters, John},
booktitle={ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
title={{QuantPipe}: Applying Adaptive Post-Training Quantization For Distributed Transformer Pipelines In Dynamic Edge Environments},
year={2023},
volume={},
number={},
pages={1-5},
doi={10.1109/ICASSP49357.2023.10096632},
ISIArea = {ML, CAS}
}
Quantifying COVID-19 policy impacts on subjective well-being during the early phase of the pandemic: A cross-sectional analysis of United States survey data from March to August 2020.
Shen, K.; and Kejriwal, M.
Plos one, 18(9): e0291494. 2023.
link
bibtex
@article{shen2023quantifying,
title={Quantifying COVID-19 policy impacts on subjective well-being during the early phase of the pandemic: A cross-sectional analysis of United States survey data from March to August 2020},
author={Shen, Ke and Kejriwal, Mayank},
journal={Plos one},
volume={18},
number={9},
pages={e0291494},
year={2023},
publisher={Public Library of Science San Francisco, CA USA}
}
Quantifying Gender Disparity in Pre-Modern English Literature using Natural Language Processing.
Kejriwal, M.; and Nagaraj, A.
Journal of Data Science,1–20. 2023.
link
bibtex
@article{kejriwal2023quantifying,
title={Quantifying Gender Disparity in Pre-Modern English Literature using Natural Language Processing},
author={Kejriwal, Mayank and Nagaraj, Akarsh},
journal={Journal of Data Science},
pages={1--20},
year={2023},
publisher={School of Statistics, Renmin University of China}
}
Quantifying confidence shifts in a BERT-based question answering system evaluated on perturbed instances.
Shen, K.; and Kejriwal, M.
Plos one, 18(12): e0295925. 2023.
link
bibtex
@article{shen2023quantifying,
title={Quantifying confidence shifts in a BERT-based question answering system evaluated on perturbed instances},
author={Shen, Ke and Kejriwal, Mayank},
journal={Plos one},
volume={18},
number={12},
pages={e0295925},
year={2023},
publisher={Public Library of Science San Francisco, CA USA}
}
RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation.
Liu, S.; Cho, H.; Freedman, M.; Ma, X.; and May, J.
In
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8404–8419, Toronto, Canada, July 2023. Association for Computational Linguistics
Paper
doi
link
bibtex
abstract
@inproceedings{liu-etal-2023-recap,
title = "{RECAP}: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation",
author = "Liu, Shuai and
Cho, Hyundong and
Freedman, Marjorie and
Ma, Xuezhe and
May, Jonathan",
booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.acl-long.468",
doi = "10.18653/v1/2023.acl-long.468",
pages = "8404--8419",
abstract = "Endowing chatbots with a consistent persona is essential to an engaging conversation, yet it remains an unresolved challenge. In this work, we propose a new retrieval-enhanced approach for personalized response generation. Specifically, we design a hierarchical transformer retriever trained on dialogue domain data to perform personalized retrieval and a context-aware prefix encoder that fuses the retrieved information to the decoder more effectively. Extensive experiments on a real-world dataset demonstrate the effectiveness of our model at generating more fluent and personalized responses. We quantitatively evaluate our model{'}s performance under a suite of human and automatic metrics and find it to be superior compared to state-of-the-art baselines on English Reddit conversations.",
}
Endowing chatbots with a consistent persona is essential to an engaging conversation, yet it remains an unresolved challenge. In this work, we propose a new retrieval-enhanced approach for personalized response generation. Specifically, we design a hierarchical transformer retriever trained on dialogue domain data to perform personalized retrieval and a context-aware prefix encoder that fuses the retrieved information to the decoder more effectively. Extensive experiments on a real-world dataset demonstrate the effectiveness of our model at generating more fluent and personalized responses. We quantitatively evaluate our model's performance under a suite of human and automatic metrics and find it to be superior compared to state-of-the-art baselines on English Reddit conversations.
RPU: A Ring Processing Unit with Applications to FHE.
Soni, D.; Neda, N.; Zhang, N.; Reynwar, B.; Heyman, B.; Moopan, M.; Badawi, A.; Polyakov, Y.; Schmidt, K. C. A. G.; Pedram, M.; Cousins, D.; French, M.; Franchetti, F.; Karri, R.; Maniatakos, M.; and Reagen, B.
In
IEEE International Symposium on Performance Analysis of Systems and Software (ISPAS2023), 2023.
link
bibtex
@inproceedings{schmidt2023_3,
author = {D. Soni and N. Neda and N. Zhang and Benedict Reynwar and B. Heyman and M. Moopan and A. Badawi and Y. Polyakov and Kellie Canidaand Anrew G. Schmidt and M. Pedram and D. Cousins and Matthew French and F. Franchetti and R. Karri and M. Maniatakos and B. Reagen},
title = {RPU: A Ring Processing Unit with Applications to FHE},
booktitle = {IEEE International Symposium on Performance Analysis of Systems and Software (ISPAS2023)},
year = {2023}}
RPU: The Ring Processor Unit.
Deepraj Soni, N. N.; Naifeng Zhang, B. R.; Homer Gamil, B. H.; Mohammed Nabeel, A. A. B.; Yuriy Polyakov, K. C.; Massoud Pedram, M. M.; David Bruce Cousins, F. F.; and Matthew French, A. S.
April 2023.
link
bibtex
@conference {Soni2023,
title = {RPU: The Ring Processor Unit},
organization = {IEEE International Symposium on Performance Analysis of Systems and Software},
year = {2023},
month = {April},
author = {Deepraj Soni, Negar Neda, Naifeng Zhang, Benedict Reynwar, Homer Gamil, Benjamin Heyman, Mohammed Nabeel, Ahmad Al Badawi, Yuriy Polyakov, Kellie Canida, Massoud Pedram, Michail Maniatakos, David Bruce Cousins, Franz Franchetti, Matthew French, Andrew Schmidt, Brandon Reagen},
ISIArea = {CAS, MES}
}
Radicalized by Thinness: Using a Model of Radicalization to Understand Pro-Anorexia Communities on Twitter.
Lerman, K.; Karnati, A.; Zhou, S.; Chen, S.; Kumar, S.; He, Z.; Yau, J.; and Horn, A.
CoRR, abs/2305.11316. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/corr/abs-2305-11316,
author = {Kristina Lerman and
Aryan Karnati and
Shuchan Zhou and
Siyi Chen and
Sudesh Kumar and
Zihao He and
Joanna Yau and
Abigail Horn},
title = {Radicalized by Thinness: Using a Model of Radicalization to Understand
Pro-Anorexia Communities on Twitter},
journal = {CoRR},
volume = {abs/2305.11316},
year = {2023},
url = {https://doi.org/10.48550/arXiv.2305.11316},
doi = {10.48550/ARXIV.2305.11316},
eprinttype = {arXiv},
eprint = {2305.11316},
timestamp = {Thu, 25 May 2023 01:00:00 +0200},
biburl = {https://dblp.org/rec/journals/corr/abs-2305-11316.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Remember what you did so you know what to do next.
Ciosici, M. R; Hedges, A.; Kankanampati, Y.; Martin, J.; Freedman, M.; and Weischedel, R.
In
Findings of the Association for Computational Linguistics: EMNLP 2023, pages 1550–1562, 2023.
link
bibtex
@inproceedings{ciosici2023remember,
title={Remember what you did so you know what to do next},
author={Ciosici, Manuel R and Hedges, Alex and Kankanampati, Yash and Martin, Justin and Freedman, Marjorie and Weischedel, Ralph},
booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023},
pages={1550--1562},
year={2023}
}
Reproducibility as a Stepping Stone to Intelligent Assistants for Data Analysis: Recreating a Study of Physical Activity, Sleep, and Work Shift in Nurses.
Brinkley, D. J.; Johnson, E.; Feng, T.; and Gil, Y.
In
Companion Proceedings of the 28th International Conference on Intelligent User Interfaces, pages 246–250, 2023.
link
bibtex
6 downloads
@inproceedings{brinkley2023reproducibility,
title={Reproducibility as a Stepping Stone to Intelligent Assistants for Data Analysis: Recreating a Study of Physical Activity, Sleep, and Work Shift in Nurses},
author={Brinkley, Detravious Jamari and Johnson, Emmanuel and Feng, Tiantian and Gil, Yolanda},
booktitle={Companion Proceedings of the 28th International Conference on Intelligent User Interfaces},
pages={246--250},
year={2023}
}
Reproducing the results for NICER observation of PSR J0030+0451.
Afle, C.; Miles, P. R.; Caino-Lores, S.; Capano, C. D.; Tews, I.; Vahi, K.; Deelman, E.; Taufer, M.; and Brown, D. A.
. 4 2023.
Funding Acknowledgments: NSF 2207264, 2041977, 2041901, 2028923, 2028930, 1841399, and 1941443; DOE DE-AC52-06NA25396
link
bibtex
@Article{ afle-arxiv-2023,
Author = "Afle, Chaitanya and Miles, Patrick R. and Caino-Lores,
Silvina and Capano, Collin D. and Tews, Ingo and Vahi,
Karan and Deelman, Ewa and Taufer, Michela and Brown,
Duncan A.",
Title = "{Reproducing the results for NICER observation of PSR
J0030+0451}",
EPrint = "2304.01035",
ArchivePrefix = "arXiv",
PrimaryClass = "astro-ph.HE",
reportnumber = "LA-UR-22-29359",
Month = "4",
Year = "2023",
Note = {Funding Acknowledgments: NSF 2207264, 2041977, 2041901,
2028923, 2028930, 1841399, and 1941443; DOE
DE-AC52-06NA25396 }
}
Revisiting Nakamoto Consensus in Asynchronous Networks: A Comprehensive Analysis of Bitcoin Safety and Chain Quality.
Saad, M.; Anwar, A.; Ravi, S.; and Mohaisen, D.
IEEE/ACM Transactions on Networking,1-15. 2023.
doi
link
bibtex
@ARTICLE{10225481,
author={Saad, Muhammad and Anwar, Afsah and Ravi, Srivatsan and Mohaisen, David},
journal={IEEE/ACM Transactions on Networking},
title={Revisiting Nakamoto Consensus in Asynchronous Networks: A Comprehensive Analysis of Bitcoin Safety and Chain Quality},
year={2023},
volume={},
number={},
pages={1-15},
keywords={Bitcoin;Blockchains;Safety;Peer-to-peer computing;Propagation delay;Delays;Security;Nakamoto consensus;Bitcoin partitioning},
doi={10.1109/TNET.2023.3302955}
}
Runtime Steering of Molecular Dynamics Simulations Through In Situ Analysis and Annotation of Collective Variables.
Caino-Lores, S.; Cuendet, M.; Marquez, J.; Kots, E.; Estrada, T.; Deelman, E.; Weinstein, H.; and Taufer, M.
In
Proceedings of the Platform for Advanced Scientific Computing Conference, of
PASC '23, New York, NY, USA, 2023. Association for Computing Machinery
Funding Acknowledgments: NSF 1741057, 1841758, 2138811 and 2223704
Paper
doi
link
bibtex
@InProceedings{ lores-pasc-2023,
Author = {Caino-Lores, Silvina and Cuendet, Michel and Marquez, Jack
and Kots, Ekaterina and Estrada, Trilce and Deelman, Ewa
and Weinstein, Harel and Taufer, Michela},
Title = {Runtime Steering of Molecular Dynamics Simulations Through
In Situ Analysis and Annotation of Collective Variables},
Year = {2023},
ISBN = {9798400701900},
Publisher = {Association for Computing Machinery},
Address = {New York, NY, USA},
URL = {https://doi.org/10.1145/3592979.3593420},
DOI = {10.1145/3592979.3593420},
BookTitle = {Proceedings of the Platform for Advanced Scientific
Computing Conference},
articleno = {21},
numpages = {11},
Keywords = {molecular dynamics, scientific workflows, collective
variables, simulation ensembles, in situ analysis},
Location = {Davos, Switzerland},
Series = {PASC '23},
Note = {Funding Acknowledgments: NSF 1741057, 1841758, 2138811 and
2223704}
}
SABAF: Removing Strong Attribute Bias from Neural Networks with Adversarial Filtering.
Li, J.; Khayatkhoei, M.; Zhu, J.; Xie, H.; Hussein, M. E; and AbdAlmageed, W.
arXiv preprint arXiv:2311.07141, November 2023.
paper
link
link
bibtex
@misc{li2023sabaf,
title={SABAF: Removing Strong Attribute Bias from Neural Networks with Adversarial Filtering},
author={Li, Jiazhi and Khayatkhoei, Mahyar and Zhu, Jiageng and Xie, Hanchen and Hussein, Mohamed E and AbdAlmageed, Wael},
Howpublished={arXiv preprint arXiv:2311.07141},
year={2023},
month={November},
url_Paper={https://arxiv.org/pdf/2311.07141.pdf},
url_Link={https://arxiv.org/abs/2311.07141},
ISIArea = {ML, VISTA}
}
SSDBM '23: Proceedings of the 35th International Conference on Scientific and Statistical Database Management.
Schuler, R.; Kesselman, C.; Chard, K.; and Bugacov, A.,
editors.
Association for Computing Machinery. New York, NY, USA, 2023.
Paper
doi
link
bibtex
@proceedings{Schuler2023c,
address = {{New York, NY, USA}},
date-added = {2024-01-22 12:05:54 -0800},
date-modified = {2024-01-22 12:05:54 -0800},
doi = {10.1145/3603719},
editor = {Schuler, Robert and Kesselman, Carl and Chard, Kyle and Bugacov, Alejandro},
isbn = {9798400707469},
publisher = {{Association for Computing Machinery}},
title = {{{SSDBM}} '23: {{Proceedings}} of the 35th {{International Conference}} on {{Scientific}} and {{Statistical Database Management}}},
url = {https://doi.org/10.1145/3603719},
year = {2023},
bdsk-url-1 = {https://doi.org/10.1145/3603719}}
10.
Orosz, M.; Duffy, B.; Charlton, C.; Saunders, H.; and Shih, M.
Scaling Agile Principles to an Enterprise, pages 201-218. John Wiley & Sons, Ltd, 2023.
Paper
doi
link
bibtex
abstract
@inbook{doi:https://doi.org/10.1002/9781394203314.ch10,
author = {Orosz, Michael and Duffy, Brian and Charlton, Craig and Saunders, Hector and Shih, Michael},
publisher = {John Wiley & Sons, Ltd},
isbn = {9781394203314},
title = {Scaling Agile Principles to an Enterprise},
booktitle = {Systems Engineering for the Digital Age},
chapter = {10},
pages = {201-218},
doi = {https://doi.org/10.1002/9781394203314.ch10},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394203314.ch10},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781394203314.ch10},
year = {2023},
keywords = {agile, scaled agile, DevSecOps, large-system acquisition, software acquisition},
abstract = {Summary Scaling agile and DevSecOps to large enterprise systems such as automotive manufacturing or space-based communication systems offers many challenges. These systems are typically composed of multiple interconnected systems and subsystems, each developed and maintained by multiple vendors operating on different timelines and priorities. The challenge to the acquisition professional is how to manage the agile development process to ensure that all components are developed as a system of systems and not as independent and isolated entities. Multiple vendors, differing timelines, delays in releases, changing requirements, the availability of reliable supply chains, and various internal and external dependencies will need to be considered. This chapter discusses the unique challenges and offers recommended strategies in scaling agile and DevSecOps to large enterprise systems with a particular focus on software-based systems. Where appropriate, reference to hardware-only or hybrid hardware- and software-based systems will also be noted.}
}
Summary Scaling agile and DevSecOps to large enterprise systems such as automotive manufacturing or space-based communication systems offers many challenges. These systems are typically composed of multiple interconnected systems and subsystems, each developed and maintained by multiple vendors operating on different timelines and priorities. The challenge to the acquisition professional is how to manage the agile development process to ensure that all components are developed as a system of systems and not as independent and isolated entities. Multiple vendors, differing timelines, delays in releases, changing requirements, the availability of reliable supply chains, and various internal and external dependencies will need to be considered. This chapter discusses the unique challenges and offers recommended strategies in scaling agile and DevSecOps to large enterprise systems with a particular focus on software-based systems. Where appropriate, reference to hardware-only or hybrid hardware- and software-based systems will also be noted.
Secure and Reliable Network Updates.
Lembke, J.; Ravi, S.; Roman, P.; and Eugster, P.
ACM Trans. Priv. Secur., 26(1): 8:1–8:41. 2023.
Paper
doi
link
bibtex
@article{DBLP:journals/tissec/LembkeRRE23,
author = {James Lembke and
Srivatsan Ravi and
Pierre{-}Louis Roman and
Patrick Eugster},
title = {Secure and Reliable Network Updates},
journal = {{ACM} Trans. Priv. Secur.},
volume = {26},
number = {1},
pages = {8:1--8:41},
year = {2023},
url = {https://doi.org/10.1145/3556542},
doi = {10.1145/3556542},
timestamp = {Mon, 05 Dec 2022 13:35:16 +0100},
biburl = {https://dblp.org/rec/journals/tissec/LembkeRRE23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Shadow Datasets, New Challenging Datasets for Causal Representation Learning.
Zhu, J.; Xie, H.; Wu, J.; Li, J.; Khayatkhoei, M.; Hussein, M. E; and AbdAlmageed, W.
arXiv preprint arXiv:2308.05707, August 2023.
paper
link
link
bibtex
@misc{zhu2023shadow,
title={Shadow Datasets, New Challenging Datasets for Causal Representation Learning},
author={Zhu, Jiageng and Xie, Hanchen and Wu, Jianhua and Li, Jiazhi and Khayatkhoei, Mahyar and Hussein, Mohamed E and AbdAlmageed, Wael},
Howpublished={arXiv preprint arXiv:2308.05707},
year={2023},
month={August},
url_Paper={https://arxiv.org/pdf/2308.05707.pdf},
url_Link={https://arxiv.org/abs/2308.05707},
ISIArea = {ML, VISTA}
}
Social Approval and Network Homophily as Motivators of Online Toxicity.
Jiang, J.; Luceri, L.; Walther, J. B; and Ferrara, E.
arXiv Preprint: https://arxiv.org/abs/2310.07779, 2023.
link
bibtex
@misc{jiang2023social,
title={Social Approval and Network Homophily as Motivators of Online Toxicity},
author={Jiang, Julie and Luceri, Luca and Walther, Joseph B and Ferrara, Emilio},
Eprint = {arXiv:2310.07779},
Howpublished = {arXiv Preprint: https://arxiv.org/abs/2310.07779},
year={2023}
}
Socio-Linguistic Characteristics of Coordinated Inauthentic Accounts.
Burghardt, K.; Rao, A.; Guo, S.; He, Z.; Chochlakis, G.; Sabyasachee, B.; Rojecki, A.; Narayanan, S.; and Lerman, K.
arXiv preprint arXiv:2305.11867. 2023.
link
bibtex
@article{burghardt2023socio,
title={Socio-Linguistic Characteristics of Coordinated Inauthentic Accounts},
author={Burghardt, Keith and Rao, Ashwin and Guo, Siyi and He, Zihao and Chochlakis, Georgios and Sabyasachee, Baruah and Rojecki, Andrew and Narayanan, Shri and Lerman, Kristina},
journal={arXiv preprint arXiv:2305.11867},
year={2023}
}
Special Issue on Artificial Intelligence and Complex Systems.
Kejriwal, M.
2023.
link
bibtex
@misc{kejriwal2023special,
title={Special Issue on Artificial Intelligence and Complex Systems},
author={Kejriwal, Mayank},
journal={Applied Sciences},
volume={13},
number={20},
pages={11153},
year={2023},
publisher={MDPI}
}
Street Rep: A Privacy-Preserving Reputation Aggregation System.
Hauser, C.; Nilizadeh, S.; Shoshitaishvili, Y.; Trieu, N.; Ravi, S.; Kruegel, C.; and Vigna, G.
IACR Cryptol. ePrint Arch.,1346. 2023.
Paper
link
bibtex
@article{DBLP:journals/iacr/HauserNSTRKV23,
author = {Christophe Hauser and
Shirin Nilizadeh and
Yan Shoshitaishvili and
Ni Trieu and
Srivatsan Ravi and
Christopher Kruegel and
Giovanni Vigna},
title = {Street Rep: {A} Privacy-Preserving Reputation Aggregation System},
journal = {{IACR} Cryptol. ePrint Arch.},
pages = {1346},
year = {2023},
url = {https://eprint.iacr.org/2023/1346},
timestamp = {Sat, 07 Oct 2023 17:43:39 +0200},
biburl = {https://dblp.org/rec/journals/iacr/HauserNSTRKV23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
Systems Engineering Agility in a Nutshell.
Dove, R.; Lunney, K.; Orosz, M.; and Yokell, M.
INSIGHT, 26(2): 11-14. 2023.
Paper
doi
link
bibtex
abstract
@article{https://doi.org/10.1002/inst.12438,
author = {Dove, Rick and Lunney, Kerry and Orosz, Michael and Yokell, Mike},
title = {Systems Engineering Agility in a Nutshell},
journal = {INSIGHT},
volume = {26},
number = {2},
pages = {11-14},
doi = {https://doi.org/10.1002/inst.12438},
url = {https://incose.onlinelibrary.wiley.com/doi/abs/10.1002/inst.12438},
eprint = {https://incose.onlinelibrary.wiley.com/doi/pdf/10.1002/inst.12438},
abstract = {ABSTRACT Systems engineering must necessarily have the agility to anticipate and effectively respond to an increasingly dynamic and uncertain environment. Agile systems engineering, agile software engineering, and agile any-kind-of engineering share common goals and leverage common agility-enabling strategies. This article succinctly describes eight strategic aspects with application discussions at the systems engineering level.},
year = {2023}
}
ABSTRACT Systems engineering must necessarily have the agility to anticipate and effectively respond to an increasingly dynamic and uncertain environment. Agile systems engineering, agile software engineering, and agile any-kind-of engineering share common goals and leverage common agility-enabling strategies. This article succinctly describes eight strategic aspects with application discussions at the systems engineering level.
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation.
Cousins, D.; Polyakov, Y.; Badawi, A.; Schmidt, A. G.; Reynwar, J. B.; Canida, K.; French, M.; A.Jaiswal; Mathew, C.; Gamil, H.; Neda, N.; Soni, D.; Maniatakos, M.; and B.Reagen
In
Government Microcircuit Applications & Critical Techology Conference (GOMACTech), 2023.
link
bibtex
@inproceedings{schmidt2023_2,
author = {D. Cousins and Y. Polyakov and A. Badawi and Andrew G. Schmidt and Justinand Benedict Reynwar and Kellie Canida and Matthew French and A.Jaiswal and C. Mathew and H. Gamil and N. Neda and D. Soni and M. Maniatakos and B.Reagen},
booktitle = {Government Microcircuit Applications \& Critical Techology Conference (GOMACTech)},
title = {TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation},
year = {2023}}
TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation.
M. French, A. S.; A. Jacob, B. R.; K. Canida, A. J.; C. Mathew, H. G.; N. Neda, D. S.; M. Maniatakos, B. R.; N. Zhang, F. F.; P. Brinich, J. J.; P. Broderick, M. F.; B. Zhang, Z. C.; M. Pedram, Y. P.; and A. Al Badawi, D. C.
March 2023.
link
bibtex
@conference {French2023a,
title = {TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation},
organization = {Government Microcircuit Applications and Critical Technology Conference (GOMACTech)},
year = {2023},
month = {March},
author = {M. French, A. Schmidt, A. Jacob, B. Reynwar, K. Canida, A. Jaiswal, C. Mathew, H. Gamil, N. Neda, D. Soni, M. Maniatakos, B. Reagen, N. Zhang, F. Franchetti, P. Brinich, J. Johnson, P. Broderick, M. Franusich, B. Zhang, Z. Cheng, M. Pedram, Y. Ployakov, A. Al Badawi, D. Cousins},
ISIArea = {CAS, MES}
}
Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning.
Lee, D.; Ahrabian, K.; Jin, W.; Morstatter, F.; and Pujara, J.
In
Conference on Empirical Methods in Natural Language Processing, 2023.
link
bibtex
@inproceedings{lee:emnlp23a,
author = "Lee, Dong-Ho and Ahrabian, Kian and Jin, Woojeong and Morstatter, Fred and Pujara, Jay",
acceptrate = "23.3\%",
arxiv_url = "https://arxiv.org/pdf/2305.10613",
bib_url = "/pubs/bib/lee-emnlp23a.bib",
booktitle = "Conference on Empirical Methods in Natural Language Processing",
code_url = "https://github.com/usc-isi-i2/isi-tkg-icl",
doi_url = "https://doi.org/10.18653/v1/2023.emnlp-main.36",
pdf_url = "/pubs/2023/lee-emnlp23a/lee-emnlp23a.pdf",
sec = "conf",
title = "Temporal Knowledge Graph Forecasting Without Knowledge Using In-Context Learning",
year = "2023"
}
The Fence Complexity of Persistent Sets.
Coccimiglio, G.; Brown, T.; and Ravi, S.
In Dolev, S.; and Schieber, B., editor(s),
Stabilization, Safety, and Security of Distributed Systems - 25th International Symposium, SSS 2023, Jersey City, NJ, USA, October 2-4, 2023, Proceedings, volume 14310, of
Lecture Notes in Computer Science, pages 36–51, 2023. Springer
Paper
doi
link
bibtex
@inproceedings{DBLP:conf/sss/CoccimiglioBR23,
author = {Gaetano Coccimiglio and
Trevor Brown and
Srivatsan Ravi},
editor = {Shlomi Dolev and
Baruch Schieber},
title = {The Fence Complexity of Persistent Sets},
booktitle = {Stabilization, Safety, and Security of Distributed Systems - 25th
International Symposium, {SSS} 2023, Jersey City, NJ, USA, October
2-4, 2023, Proceedings},
series = {Lecture Notes in Computer Science},
volume = {14310},
pages = {36--51},
publisher = {Springer},
year = {2023},
url = {https://doi.org/10.1007/978-3-031-44274-2\_3},
doi = {10.1007/978-3-031-44274-2\_3},
timestamp = {Sun, 08 Oct 2023 13:20:04 +0200},
biburl = {https://dblp.org/rec/conf/sss/CoccimiglioBR23.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
The Prevalence of Single Sign-On on the Web: Towards the Next Generation of Web Content Measurement.
Ardi, C.; and Calder, M.
In
Proceedings of the 2023 ACM on Internet Measurement Conference, of
IMC '23, pages 124–130, New York, NY, USA, 2023. Association for Computing Machinery
Paper
doi
link
bibtex
abstract
@inproceedings{10.1145/3618257.3624841,
author = {Ardi, Calvin and Calder, Matt},
title = {The Prevalence of Single Sign-On on the Web: Towards the Next Generation of Web Content Measurement},
year = {2023},
isbn = {9798400703829},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3618257.3624841},
doi = {10.1145/3618257.3624841},
abstract = {Much of the content and structure of the Web remains inaccessible to evaluate at scale because it is gated by user authentication. This limitation restricts researchers to examining only a superficial layer of a website: the landing page or public, search-indexable pages. Since it is infeasible to create individual accounts across thousands of webpages, we examine the prevalence of Single Sign-On (SSO) on the web to explore the feasibility of using a few accounts to authenticate to many sites. We find that 58\% of the top 10K websites with logins are accessible with popular 3rd-party SSO providers, such as Google, Facebook, and Apple, indicating that leveraging SSO offers a scalable solution to access a large volume of user-gated content.},
booktitle = {Proceedings of the 2023 ACM on Internet Measurement Conference},
pages = {124–130},
numpages = {7},
keywords = {web measurement, web authentication, top lists, single sign-on},
location = {Montreal QC, Canada},
series = {IMC '23}
}
Much of the content and structure of the Web remains inaccessible to evaluate at scale because it is gated by user authentication. This limitation restricts researchers to examining only a superficial layer of a website: the landing page or public, search-indexable pages. Since it is infeasible to create individual accounts across thousands of webpages, we examine the prevalence of Single Sign-On (SSO) on the web to explore the feasibility of using a few accounts to authenticate to many sites. We find that 58% of the top 10K websites with logins are accessible with popular 3rd-party SSO providers, such as Google, Facebook, and Apple, indicating that leveraging SSO offers a scalable solution to access a large volume of user-gated content.
The Unequal Opportunities of Large Language Models: Examining Demographic Biases in Job Recommendations by ChatGPT and LLaMA.
Salinas, A.; Shah, P.; Huang, Y.; McCormack, R.; and Morstatter, F.
In
Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, pages 1–15, 2023.
link
bibtex
@inproceedings{salinas2023unequal,
title={The Unequal Opportunities of Large Language Models: Examining Demographic Biases in Job Recommendations by ChatGPT and LLaMA},
author={Salinas, Abel and Shah, Parth and Huang, Yuzhong and McCormack, Robert and Morstatter, Fred},
booktitle={Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization},
pages={1--15},
year={2023}
}
The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages.
Akerman, V.; Baines, D.; Daspit, D.; Hermjakob, U.; Jang, T.; Leong, C.; Martin, M.; Mathew, J.; Robie, J.; and Schwarting, M.
2023.
link
bibtex
@misc{akerman2023ebible,
title={The eBible Corpus: Data and Model Benchmarks for Bible Translation for Low-Resource Languages},
author={Vesa Akerman and David Baines and Damien Daspit and Ulf Hermjakob and Taeho Jang and Colin Leong and Michael Martin and Joel Mathew and Jonathan Robie and Marcus Schwarting},
year={2023},
eprint={2304.09919},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
The interconnected nature of online harm and moderation: investigating the cross-platform spread of harmful content between youtube and Twitter.
Gatta, V. L.; Luceri, L.; Fabbri, F.; and Ferrara, E.
In
Proceedings of the 34th ACM conference on hypertext and social media, 2023.
link
bibtex
@inproceedings{gatta2023interconnected,
title={The interconnected nature of online harm and moderation: investigating the cross-platform spread of harmful content between youtube and Twitter},
author={Gatta, Valerio La and Luceri, Luca and Fabbri, Francesco and Ferrara, Emilio},
booktitle={Proceedings of the 34th ACM conference on hypertext and social media},
year={2023}
}
Tighter Prediction Intervals for Causal Outcomes Under Hidden Confounding.
Marmarelis, M. G; Steeg, G. V.; Galstyan, A.; and Morstatter, F.
arXiv preprint arXiv:2306.09520. 2023.
link
bibtex
@article{marmarelis2023tighter,
title={Tighter Prediction Intervals for Causal Outcomes Under Hidden Confounding},
author={Marmarelis, Myrl G and Steeg, Greg Ver and Galstyan, Aram and Morstatter, Fred},
journal={arXiv preprint arXiv:2306.09520},
year={2023}
}
Towards Effective Multi-Valued Heuristics for Bi-Objective Shortest-Path Algorithms via Differential Heuristics.
Zhang, H.; Salzman, O.; Felner, A.; Thittamaranahalli, S.; Skyler, S.; Hernandez, C.; and Koenig, S.
Proceedings of the Sixteenth International Symposium on Combinatorial Search (SOCS-2023). 2023.
link
bibtex
@article{tksk04,
author={Han Zhang and Oren Salzman and Ariel Felner and Satish Thittamaranahalli and Shawn Skyler and Carlos Hernandez and Sven Koenig},
title={Towards Effective Multi-Valued Heuristics for Bi-Objective Shortest-Path Algorithms via Differential Heuristics},
journal={Proceedings of the Sixteenth International Symposium on Combinatorial Search (SOCS-2023)},
year={2023}
}
Towards Reflection Competencies in Intelligent Systems for Science.
Gil, Y.
In
Artificial Intelligence for Science: A Deep Learning Revolution. World Scientific, London, UK, 2023.
Link
Paper
link
bibtex
14 downloads
@incollection{gil-chapter-23,
title = {Towards Reflection Competencies in Intelligent Systems for Science},
author = {Yolanda Gil},
year = {2023},
booktitle = {Artificial Intelligence for Science: A Deep Learning Revolution},
editors = {Alok Choudhary and Geoffrey Fox and Tony Hey},
publisher = {World Scientific, London, UK},
ee = {https://doi.org/10.1142/13123},
url = {https://knowledgecaptureanddiscovery.github.io/yolanda_gil_website/papers/Gil-Chapter-2023.pdf}
}
Toxic Bias: Perspective API misreads German as more toxic.
Nogara, G.; Pierri, F.; Cresci, S.; Luceri, L.; Törnberg, P.; and Giordano, S.
arXiv Preprint: https://arxiv.org/abs/2312.12651, 2023.
link
bibtex
@misc{nogara2023toxic,
title={Toxic Bias: Perspective API misreads German as more toxic},
author={Nogara, Gianluca and Pierri, Francesco and Cresci, Stefano and Luceri, Luca and T{\"o}rnberg, Petter and Giordano, Silvia},
Eprint = {arXiv:2312.12651},
Howpublished = {arXiv Preprint: https://arxiv.org/abs/2312.12651},
year={2023}
}
TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization.
Nandi, S.; Natarajan, P.; and Abd-Almageed, W.
In
Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 403–414, 2023.
link
bibtex
@inproceedings{nandi2023trainfors,
title={TrainFors: A Large Benchmark Training Dataset for Image Manipulation Detection and Localization},
author={Nandi, Soumyaroop and Natarajan, Prem and Abd-Almageed, Wael},
booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
pages={403--414},
year={2023}
}
Transfer Learning with Prior Data-Driven Models from Multiple Unconventional Fields.
Cornelio, J.; Mohd Razak, S.; Cho, Y.; Liu, H.; Vaidya, R.; and Jafarpour, B.
SPE Journal,1–30. 2023.
Publisher: SPE
Paper
link
bibtex
@article{cornelio_transfer_2023,
title = {Transfer {Learning} with {Prior} {Data}-{Driven} {Models} from {Multiple} {Unconventional} {Fields}},
url = {https://onepetro.org/SJ/article-abstract/doi/10.2118/214312-PA/519406},
urldate = {2024-02-12},
journal = {SPE Journal},
author = {Cornelio, Jodel and Mohd Razak, Syamil and Cho, Young and Liu, Hui-Hai and Vaidya, Ravimadhav and Jafarpour, Behnam},
year = {2023},
note = {Publisher: SPE},
pages = {1--30},
}
Trojan Model Detection Using Activation Optimization.
Hussein, M. E.; Janakiraman, S. S.; and AbdAlmageed, W.
arXiv Preprint: http://arxiv.org/abs/2306.04877, 2023.
link
bibtex
@misc{hussein2023trojan,
title={Trojan Model Detection Using Activation Optimization},
author={Mohamed E. Hussein and Sudharshan Subramaniam Janakiraman and Wael AbdAlmageed},
year={2023},
eprint={2306.04877},
archivePrefix={arXiv},
primaryClass={cs.CV},
howpublished={arXiv Preprint: http://arxiv.org/abs/2306.04877}
}
Understanding and Estimating Domain Complexity Across Domains.
Doctor, K.; Kejriwal, M.; Holder, L.; Kildebeck, E.; Resmini, E.; Pereyda, C.; Steininger, R. J; and Olivença, D. V
arXiv preprint arXiv:2312.13487. 2023.
link
bibtex
@article{doctor2023understanding,
title={Understanding and Estimating Domain Complexity Across Domains},
author={Doctor, Katarina and Kejriwal, Mayank and Holder, Lawrence and Kildebeck, Eric and Resmini, Emma and Pereyda, Christopher and Steininger, Robert J and Oliven{\c{c}}a, Daniel V},
journal={arXiv preprint arXiv:2312.13487},
year={2023}
}
31.
Orosz, M.; Duffy, B.; Charlton, C.; Saunders, H.; and Thomas, E.
Unique Challenges in Mission Engineering and Technology Integration, pages 665-681. John Wiley & Sons, Ltd, 2023.
Paper
doi
link
bibtex
abstract
@inbook{doi:https://doi.org/10.1002/9781394203314.ch31,
author = {Orosz, Michael and Duffy, Brian and Charlton, Craig and Saunders, Hector and Thomas, Ellins},
publisher = {John Wiley & Sons, Ltd},
isbn = {9781394203314},
title = {Unique Challenges in Mission Engineering and Technology Integration},
booktitle = {Systems Engineering for the Digital Age},
chapter = {31},
pages = {665-681},
doi = {https://doi.org/10.1002/9781394203314.ch31},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394203314.ch31},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781394203314.ch31},
year = {2023},
keywords = {digital engineering, DevSecOps, model-based systems engineering, MBSE, large-system acquisition, software acquisition},
abstract = {Summary Undertaking mission engineering and technology integration in large enterprise systems such as automotive manufacturing or space-based communication systems offer many challenges. These systems are typically composed of multiple interconnected systems and subsystems, each developed and maintained by multiple vendors operating on different timelines and priorities. Mission engineering refers to applying systems engineering processes and principles to the complete product lifecycle – requirements analysis, design, development, integration, testing, deployment, and sustainment of a complex systems of systems project. Such processes and principles include DevSecOps, digital engineering, model-based systems engineering (MBSE), Agile and other systems design and development processes. Technology integration refers to the processes and principles of inserting technology into both the engineering and development processes of a system's acquisition program. Examples of technology insertion include adding or expanding system requirements to meet changing market conditions or reacting to changing operating environments. This chapter discusses the unique challenges and offers recommended strategies in undertaking mission engineering and technology insertion in large enterprise systems with a particular focus on software-based systems. Where appropriate, reference to hardware-only or hybrid hardware and software-based systems will also be noted.}
}
Summary Undertaking mission engineering and technology integration in large enterprise systems such as automotive manufacturing or space-based communication systems offer many challenges. These systems are typically composed of multiple interconnected systems and subsystems, each developed and maintained by multiple vendors operating on different timelines and priorities. Mission engineering refers to applying systems engineering processes and principles to the complete product lifecycle – requirements analysis, design, development, integration, testing, deployment, and sustainment of a complex systems of systems project. Such processes and principles include DevSecOps, digital engineering, model-based systems engineering (MBSE), Agile and other systems design and development processes. Technology integration refers to the processes and principles of inserting technology into both the engineering and development processes of a system's acquisition program. Examples of technology insertion include adding or expanding system requirements to meet changing market conditions or reacting to changing operating environments. This chapter discusses the unique challenges and offers recommended strategies in undertaking mission engineering and technology insertion in large enterprise systems with a particular focus on software-based systems. Where appropriate, reference to hardware-only or hybrid hardware and software-based systems will also be noted.
Unsupervised Multimodal Deepfake Detection Using Intra- and Cross-Modal Inconsistencies.
Tian, M.; Khayatkhoei, M.; Mathai, J.; and AbdAlmageed, W.
arXiv preprint arXiv:2311.17088, November 2023.
paper
link
link
bibtex
@misc{tian2023unsupervised,
title={Unsupervised Multimodal Deepfake Detection Using Intra- and Cross-Modal Inconsistencies},
author={Tian, Mulin and Khayatkhoei, Mahyar and Mathai, Joe and AbdAlmageed, Wael},
Howpublished={arXiv preprint arXiv:2311.17088},
year={2023},
month={November},
url_Paper={https://arxiv.org/pdf/2311.17088.pdf},
url_Link={https://arxiv.org/abs/2311.17088},
ISIArea = {ML, VISTA}
}
Unveiling the Dynamics of Censorship, COVID-19 Regulations, and Protest: An Empirical Study of Chinese Subreddit r/china_irl.
Zhou, S.; Luceri, L.; and Ferrara, E.
In
AAAI ICWSM Workshop, 2023.
link
bibtex
@inproceedings{zhou2023unveiling,
title={Unveiling the Dynamics of Censorship, COVID-19 Regulations, and Protest: An Empirical Study of Chinese Subreddit r/china\_irl},
author={Zhou, Siyi and Luceri, Luca and Ferrara, Emilio},
booktitle={AAAI ICWSM Workshop},
year={2023}
}
Using conditional inference to quantify interaction effects of socio-demographic covariates of US COVID-19 vaccine hesitancy.
Shen, K.; and Kejriwal, M.
PLOS Global Public Health, 3(5): e0001151. 2023.
link
bibtex
@article{shen2023using,
title={Using conditional inference to quantify interaction effects of socio-demographic covariates of US COVID-19 vaccine hesitancy},
author={Shen, Ke and Kejriwal, Mayank},
journal={PLOS Global Public Health},
volume={3},
number={5},
pages={e0001151},
year={2023},
publisher={Public Library of Science San Francisco, CA USA}
}
VisDict: Improving Communication Via a Visual Dictionary in a Science Gateway.
Gesing, S.; Deelman, E.; Hildreth, M.; Makhija, R.; McDowell, M. A.; Meyers, N. K.; and Thain, D.
Computing in Science & Engineering, 25(2): 7-11. 2023.
Funding Acknowledgments: NSF 2216851, 2100561, and 2100636
doi
link
bibtex
@Article{ gesing-cise-2023,
Author = {Gesing, Sandra and Deelman, Ewa and Hildreth, Michael and
Makhija, Ramandeep and McDowell, Mary Ann and Meyers,
Natalie K. and Thain, Douglas},
Journal = {Computing in Science & Engineering},
Title = {VisDict: Improving Communication Via a Visual Dictionary
in a Science Gateway},
Year = {2023},
Volume = {25},
Number = {2},
Pages = {7-11},
DOI = {10.1109/MCSE.2023.3275711},
Note = {Funding Acknowledgments: NSF 2216851, 2100561, and 2100636
}
}
Visual Cropping Improves Zero-Shot Question Answering of Multimodal Large Language Models.
Zhang, J.; Khayatkhoei, M.; Chhikara, P.; and Ilievski, F.
In
Advances in Neural Information Processing Systems Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models, December 2023.
paper
link
link
bibtex
@InProceedings{zhang2023visual-crop,
title={Visual Cropping Improves Zero-Shot Question Answering of Multimodal Large Language Models},
author={Zhang, Jiarui and Khayatkhoei, Mahyar and Chhikara, Prateek and Ilievski, Filip},
booktitle={Advances in Neural Information Processing Systems Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models},
year={2023},
month={December},
url_Paper={https://openreview.net/pdf?id=YrYcoV2dAk},
url_Link={https://neurips.cc/virtual/2023/76680},
ISIArea = {ML, VISTA, NLP}
}
What Is The Internet? Partial Connectivity of the Internet Core.
Baltra, G.; and Heidemann, J.
Technical Report arXiv:2107.11439v3, USC/Information Sciences Institute, March 2023.
Paper
doi
link
bibtex
abstract
@TechReport{Baltra23a,
author = "Guillermo Baltra and John Heidemann",
title = "What Is The {Internet}? Partial Connectivity
of the Internet Core",
institution = "USC/Information Sciences Institute",
year = 2023,
sortdate = "2023-03-20",
project = "ant, eieio, minceq",
jsubject = "routing",
notes = "released 2021-07-23, updated 2022-05-24, v3 update 2023-03-20",
number = "arXiv:2107.11439v3",
month = mar,
jlocation = "johnh: pafile",
keywords = "trinocular, outages, partial outages",
url = "https://ant.isi.edu/%7ejohnh/PAPERS/Baltra23a.html",
pdfurl = "https://ant.isi.edu/%7ejohnh/PAPERS/Baltra23a.pdf",
doi = "https://doi.org/10.48550/2107.11439v3",
myorganization = "USC/Information Sciences Institute",
copyrightholder = "authors",
abstract = "
``A collection of interconnected networks'' defines what the Internet is, but not what it is not. Events threaten Internet fragmentation: politics suggest countries or ISPs may secede or be de-peered, disputes between ISPs result in persistent unreachability between their customers, and architectural changes risk breaking the ``one'' Internet. Understanding such threats benefits from a testable definition of what the Internet is and is not, enabling discussion and quantification of partial connectivity. We provide a conceptual definition giving an idealized asymptote of connectivity. It implies peninsulas of persistent, partial connectivity, and islands when one or more computers are partitioned from the main Internet. We provide algorithms to measure, operationally, the number, size, and duration of peninsulas and islands. We apply these algorithms in rigorous measurement from two complementary measurement systems, one observing 5M networks from a few locations, and the other a few destinations from 10k locations. Results show that peninsulas (partial connectivity) are about as common as Internet outages, quantifying this long-observed problem. Root causes show that most peninsula events (45\%) are routing transients, but most peninsula-time (90\%) is from a few long-lived events (7\%). Our analysis helps interpret DNSmon, a system monitoring the DNS root, separating measurement error and persistent problems from underlying differences and operationally important transients. Finally, our definition confirms the international nature of the Internet: no single country can unilaterally claim to be ``the Internet'', but countries can choose to leave.
",
}
``A collection of interconnected networks'' defines what the Internet is, but not what it is not. Events threaten Internet fragmentation: politics suggest countries or ISPs may secede or be de-peered, disputes between ISPs result in persistent unreachability between their customers, and architectural changes risk breaking the ``one'' Internet. Understanding such threats benefits from a testable definition of what the Internet is and is not, enabling discussion and quantification of partial connectivity. We provide a conceptual definition giving an idealized asymptote of connectivity. It implies peninsulas of persistent, partial connectivity, and islands when one or more computers are partitioned from the main Internet. We provide algorithms to measure, operationally, the number, size, and duration of peninsulas and islands. We apply these algorithms in rigorous measurement from two complementary measurement systems, one observing 5M networks from a few locations, and the other a few destinations from 10k locations. Results show that peninsulas (partial connectivity) are about as common as Internet outages, quantifying this long-observed problem. Root causes show that most peninsula events (45%) are routing transients, but most peninsula-time (90%) is from a few long-lived events (7%). Our analysis helps interpret DNSmon, a system monitoring the DNS root, separating measurement error and persistent problems from underlying differences and operationally important transients. Finally, our definition confirms the international nature of the Internet: no single country can unilaterally claim to be ``the Internet'', but countries can choose to leave.
XMD: An End-to-End Framework for Interactive Explanation-Based Debugging of NLP Models.
Lee, D.; Kadakia, A.; Joshi, B.; Chan, A.; Liu, Z.; Narahari, K.; Shibuya, T.; Mitani, R.; Sekiya, T.; Pujara, J.; and Ren, X.
In
Association for Computational Linguistics, 2023.
link
bibtex
@inproceedings{lee:acl23,
author = "Lee, Dong-Ho and Kadakia, Akshen and Joshi, Brihi and Chan, Aaron and Liu, Ziyi and Narahari, Kiran and Shibuya, Takashi and Mitani, Ryosuke and Sekiya, Toshiyuki and Pujara, Jay and Ren, Xiang",
acceptrate = "37\%",
bib_url = "/pubs/bib/lee-acl23.bib",
booktitle = "Association for Computational Linguistics",
doi_url = "http://dx.doi.org/10.18653/v1/2023.acl-demo.25",
pdf_url = "/pubs/2023/lee-acl23/lee-acl23.pdf",
sec = "conf",
title = "{XMD}: An End-to-End Framework for Interactive Explanation-Based Debugging of {NLP} Models",
year = "2023"
}
cfr (v2023.9.14): a Python package for climate field reconstruction.
Zhu, F.; Emile-Geay, J.; Hakim, G. J.; Guillot, D.; Khider, D.; Tardif, R.; and Perkins, W. A.
Technical Report Climate and Earth system modeling, September 2023.
Paper
doi
link
bibtex
abstract
1 download
@techreport{zhu_cfr_2023,
type = {preprint},
title = {cfr (v2023.9.14): a {Python} package for climate field reconstruction},
shorttitle = {cfr (v2023.9.14)},
url = {https://egusphere.copernicus.org/preprints/2023/egusphere-2023-2098/},
abstract = {Abstract. Climate field reconstruction (CFR) refers to the estimation of spatiotemporal climate fields (such as surface temperature) from a collection of pointwise paleoclimate proxy datasets. The climate fields can provide rich information on climate dynamics and provide an out-of-sample validation of climate models. However, most CFR workflows are complex and timeconsuming, as they involve: (i) preprocessing of the proxy records, climate model simulations, and instrumental observations, (ii) application of one or more statistical methods, and (iii) analysis and visualization of the reconstruction results. Historically, this process has lacked transparency and accessibility, limiting reproducibility and experimentation by non-specialists. This article presents an open-source and object-oriented Python package called cfr that aims to make CFR workflows easy to understand and conduct, saving climatologists from technical details and facilitating efficient and reproducible research. It provides user-friendly utilities for common CFR tasks such as proxy and climate data analysis and visualization, proxy system modeling, and modularized workflows for multiple reconstruction methods, enabling methodological intercomparisons within the same framework. The package is supported with an extensive documentation of the application interface (API) and a growing number of tutorial notebooks illustrating its usage. As an example, we present two cfr-driven reconstruction experiments using the PAGES 2k temperature database: applying the last millennium reanalysis (LMR) paleoclimate data assimilation (PDA) framework and the Graphical Expectation-Maximization (GraphEM) algorithm, respectively.},
urldate = {2023-11-17},
institution = {Climate and Earth system modeling},
author = {Zhu, Feng and Emile-Geay, Julien and Hakim, Gregory J. and Guillot, Dominique and Khider, Deborah and Tardif, Robert and Perkins, Walter A.},
month = sep,
year = {2023},
doi = {10.5194/egusphere-2023-2098},
}
Abstract. Climate field reconstruction (CFR) refers to the estimation of spatiotemporal climate fields (such as surface temperature) from a collection of pointwise paleoclimate proxy datasets. The climate fields can provide rich information on climate dynamics and provide an out-of-sample validation of climate models. However, most CFR workflows are complex and timeconsuming, as they involve: (i) preprocessing of the proxy records, climate model simulations, and instrumental observations, (ii) application of one or more statistical methods, and (iii) analysis and visualization of the reconstruction results. Historically, this process has lacked transparency and accessibility, limiting reproducibility and experimentation by non-specialists. This article presents an open-source and object-oriented Python package called cfr that aims to make CFR workflows easy to understand and conduct, saving climatologists from technical details and facilitating efficient and reproducible research. It provides user-friendly utilities for common CFR tasks such as proxy and climate data analysis and visualization, proxy system modeling, and modularized workflows for multiple reconstruction methods, enabling methodological intercomparisons within the same framework. The package is supported with an extensive documentation of the application interface (API) and a growing number of tutorial notebooks illustrating its usage. As an example, we present two cfr-driven reconstruction experiments using the PAGES 2k temperature database: applying the last millennium reanalysis (LMR) paleoclimate data assimilation (PDA) framework and the Graphical Expectation-Maximization (GraphEM) algorithm, respectively.
seq2seq-SC: End-to-End Semantic Communication Systems with Pre-Trained Language Models.
Lee, J.; Lee, D.; Sheen, E.; Choi, T.; Pujara, J.; and Kim, J.
In
Asilomar Conference on Signals, Systems, and Computers, 2023.
link
bibtex
@inproceedings{lee:asilomar23,
Author = "Lee, Ju-Hyung and Lee, Dong-Ho and Sheen, Eunsoo and Choi, Thomas and Pujara, Jay and Kim, Joongheon",
booktitle = "Asilomar Conference on Signals, Systems, and Computers",
sec = "conf",
title = "seq2seq-SC: End-to-End Semantic Communication Systems with Pre-Trained Language Models",
year = "2023"
}
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abstract
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Slides
link
bibtex
abstract
4 downloads
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Slides
link
bibtex
abstract
4 downloads