{"id":11,"date":"2023-10-13T16:13:20","date_gmt":"2023-10-13T16:13:20","guid":{"rendered":"https:\/\/www.isi.edu\/people-galstyan\/?page_id=11"},"modified":"2025-06-13T17:43:35","modified_gmt":"2025-06-13T17:43:35","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.isi.edu\/people-galstyan\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n\n\t\n
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2026<\/h2>\n \n
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\n \n AutoSUIT Bench-Automated Security UnIt Test Benchmark for LLM Coding <\/a>\n <\/h3>\n\n
\n Samuel Osebe, Fan Yang, Junyi Li, Yue Gu, Yongxin Wang, Satyapriya Krishna, Kai-Wei Chang, Aram Galstyan, Rahul Gupta, Weitong Ruan <\/div>\n \n
\n Findings of the Association for Computational Linguistics: ACL 2026, 34759-34783<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Sparrow: Sparse Rollout for Stable and Efficient Long-context RL of Large Language Models <\/a>\n <\/h3>\n\n
\n Yang Zhou, Ranajoy Sadhukhan, Zhaofeng Sun, Zhuoming Chen, Souvik Kundu, Saket Dingliwal, Sai Muralidhar Jayanthi, Aram Galstyan, Haizhong Zheng, Beidi Chen <\/div>\n \n
\n arXiv preprint arXiv:2606.08446<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n SWAN: Semantic Watermarking with Abstract Meaning Representation <\/a>\n <\/h3>\n\n
\n Ziping Ye, Gourab Dey, Christos Christodoulopoulos, Charith Peris, Anil Ramakrishna, Weitong Ruan, Aram Galstyan, Kai-Wei Chang, Rahul Gupta, Ninareh Mehrabi <\/div>\n \n
\n arXiv preprint arXiv:2605.04305<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n ExComm: Exploration-Stage Communication for Error-Resilient Agentic Test-Time Scaling <\/a>\n <\/h3>\n\n
\n Woomin Song, Beomjun Kim, Daewon Choi, Sai Muralidhar Jayanthi, Saket Dingliwal, Jinwoo Shin, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2605.22102<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n IdleSpec: Exploiting Idle Time via Speculative Planning for LLM Agents <\/a>\n <\/h3>\n\n
\n Daewon Choi, Kyunghyun Park, Woomin Song, Saket Dingliwal, Sai Muralidhar Jayanthi, Jinwoo Shin, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2605.22154<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n RoPE Distinguishes Neither Positions Nor Tokens in Long Contexts, Provably <\/a>\n <\/h3>\n\n
\n Yufeng Du, Phillip Harris, Minyang Tian, Eliu A Huerta, Srikanth Ronanki, Subendhu Rongali, Aram Galstyan, Hao Peng <\/div>\n \n
\n arXiv preprint arXiv:2605.15514<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Emergent Strategic Reasoning Risks in AI: A Taxonomy-Driven Evaluation Framework <\/a>\n <\/h3>\n\n
\n Tharindu Kumarage, Lisa Bauer, Yao Ma, Dan Rosen, Yashasvi Raghavendra Guduri, Anna Rumshisky, Kai-Wei Chang, Aram Galstyan, Rahul Gupta, Charith Peris <\/div>\n \n
\n arXiv preprint arXiv:2604.22119<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n ARES: Adaptive Red-Teaming and End-to-End Repair of Policy-Reward System <\/a>\n <\/h3>\n\n
\n Jiacheng Liang, Yao Ma, Tharindu Kumarage, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Aram Galstyan, Charith Peris <\/div>\n \n
\n arXiv preprint arXiv:2604.18789<\/i>, 2026\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2025<\/h2>\n \n
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\n \n Accelerated Test-Time Scaling with Model-Free Speculative Sampling <\/a>\n <\/h3>\n\n
\n Woomin Song, Saket Dingliwal, Sai Muralidhar Jayanthi, Bhavana Ganesh, Jinwoo Shin, Aram Galstyan, Sravan Babu Bodapati <\/div>\n \n
\n arXiv preprint arXiv:2506.04708<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Kaleidoscopic Teaming in Multi Agent Simulations <\/a>\n <\/h3>\n\n
\n Ninareh Mehrabi, Tharindu Kumarage, Kai-Wei Chang, Aram Galstyan, Rahul Gupta <\/div>\n \n
\n arXiv preprint arXiv:2506.17514<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Think Clearly: Improving Reasoning via Redundant Token Pruning <\/a>\n <\/h3>\n\n
\n Daewon Choi, Jimin Lee, Jihoon Tack, Woomin Song, Saket Dingliwal, Sai Muralidhar Jayanthi, Bhavana Ganesh, Jinwoo Shin, Aram Galstyan, Sravan Babu Bodapati <\/div>\n \n
\n arXiv preprint arXiv:2507.08806<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Mamba Drafters for Speculative Decoding <\/a>\n <\/h3>\n\n
\n Daewon Choi, Seunghyuk Oh, Saket Dingliwal, Jihoon Tack, Kyuyoung Kim, Woomin Song, Seojin Kim, Insu Han, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati <\/div>\n \n
\n arXiv preprint arXiv:2506.01206<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Compress, Gather, and Recompute: REFORMing Long-Context Processing in Transformers <\/a>\n <\/h3>\n\n
\n Woomin Song, Sai Muralidhar Jayanthi, Srikanth Ronanki, Kanthashree Mysore Sathyendra, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati <\/div>\n \n
\n arXiv preprint arXiv:2506.01215<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Towards Safety Reasoning in LLMs: AI-agentic Deliberation for Policy-embedded CoT Data Creation <\/a>\n <\/h3>\n\n
\n Tharindu Kumarage, Ninareh Mehrabi, Anil Ramakrishna, Xinyan Zhao, Richard Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta, Charith Peris <\/div>\n \n
\n arXiv preprint arXiv:2505.21784<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n KG-LLM-Bench: A Scalable Benchmark for Evaluating LLM Reasoning on Textualized Knowledge Graphs <\/a>\n <\/h3>\n\n
\n Elan Markowitz, Krupa Galiya, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2504.07087<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application <\/a>\n <\/h3>\n\n
\n Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Zheng Chen, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n ICASSP 2025-2025 IEEE International Conference on Acoustics, Speech and \u2026<\/i>, 2025\n\n <\/div>\n\n <\/div>\n\n \n
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\n \n Wanda++: Pruning Large Language Models via Regional Gradients <\/a>\n <\/h3>\n\n
\n Yifan Yang, Kai Zhen, Bhavana Ganesh, Aram Galstyan, Goeric Huybrechts, Markus M\u00fcller, Jonas M K\u00fcbler, Rupak Vignesh Swaminathan, Athanasios Mouchtaris, Sravan Babu Bodapati, Nathan Susanj, Zheng Zhang, Jack FitzGerald, Abhishek Kumar <\/div>\n \n
\n arXiv preprint arXiv:2503.04992<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n K-Edit: Language Model Editing with Contextual Knowledge Awareness <\/a>\n <\/h3>\n\n
\n Elan Markowitz, Anil Ramakrishna, Ninareh Mehrabi, Charith Peris, Rahul Gupta, Kai-Wei Chang, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2502.10626<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Context Length Alone Hurts LLM Performance Despite Perfect Retrieval <\/a>\n <\/h3>\n\n
\n Yufeng Du, Minyang Tian, Srikanth Ronanki, Subendhu Rongali, Sravan Bodapati, Aram Galstyan, Azton Wells, Roy Schwartz, Eliu A Huerta, Hao Peng <\/div>\n \n
\n arXiv preprint arXiv:2510.05381<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Natural language question generation <\/a>\n <\/h3>\n\n
\n A Kumar, Y Fung, P Natarajan, A Galstyan, H Ji <\/div>\n \n
\n US Patent 12,456,015<\/i>, 2025\n\n <\/div>\n\n <\/div>\n\n \n
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\n \n Systems and methods for updating large language models <\/a>\n <\/h3>\n\n
\n K Mishra, T Soliman, A Galstyan, A Kumar, AK Ramakrishna <\/div>\n \n
\n US Patent 12,456,020<\/i>, 2025\n\n <\/div>\n\n <\/div>\n\n \n
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\n \n SeRA: Self-reviewing and alignment of LLMs using implicit reward margins <\/a>\n <\/h3>\n\n
\n Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh, Sailik Sengupta, Sravan Babu Bodapati, Aram Galstyan <\/div>\n \n
\n The Thirteenth International Conference on Learning Representations<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n SGD-KV: Summarization Guided KV Cache Compression <\/a>\n <\/h3>\n\n
\n Zeyu Liu, Woomin Song, Xuandi Fu, Sai Muralidhar Jayanthi, Vivek Govindan, Aram Galstyan, Sravan Babu Bodapati, Srikanth Ronanki <\/div>\n \n
\n NeurIPS 2025 Workshop on Efficient Reasoning<\/i>, 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n On localizing and deleting toxic memories in large language models <\/a>\n <\/h3>\n\n
\n Anubrata Das, Manoj Kumar, Ninareh Mehrabi, Anil Ramakrishna, Anna Rumshisky, Kai-Wei Chang, Aram Galstyan, Morteza Ziyadi, Rahul Gupta <\/div>\n \n
\n 2025\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2024<\/h2>\n \n
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\n \n Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs <\/a>\n <\/h3>\n\n
\n Elan Markowitz, Anil Ramakrishna, Jwala Dhamala, Ninareh Mehrabi, Charith Peris, Rahul Gupta, Kai-Wei Chang, Aram Galstyan <\/div>\n \n
\n ACL'24<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Leveraging LLMs for dialogue quality measurement <\/a>\n <\/h3>\n\n
\n Jinghan Jia, Abi Komma, Timothy Leffel, Xujun Peng, Ajay Nagesh, Tamer Soliman, Aram Galstyan, Anoop Kumar <\/div>\n \n
\n 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Proceedings of the 4th Workshop on Trustworthy Natural Language Processing (TrustNLP 2024) <\/a>\n <\/h3>\n\n
\n Kai-Wei Chang, Anaelia Ovalle, Jieyu Zhao, Yang Trista Cao, Ninareh Mehrabi, Aram Galstyan, Jwala Dhamala, Anoop Kumar, Rahul Gupta <\/div>\n \n
\n Proceedings of the 4th Workshop on Trustworthy Natural Language Processing \u2026<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n MICo: Preventative detoxification of large language models through inhibition control <\/a>\n <\/h3>\n\n
\n Roy Siegelmann, Ninareh Mehrabi, Palash Goyal, Prasoon Goyal, Lisa Bauer, Jwala Dhamala, Aram Galstyan, Rahul Gupta, Reza Ghanadan <\/div>\n \n
\n Findings of the Association for Computational Linguistics: NAACL 2024, 1696-1703<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Believe: Belief-enhanced instruction generation and augmentation for zero-shot bias mitigation <\/a>\n <\/h3>\n\n
\n Lisa Bauer, Ninareh Mehrabi, Palash Goyal, Kai-Wei Chang, Aram Galstyan, Rahul Gupta <\/div>\n \n
\n 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Agenda-Driven Question Generation: A Case Study in the Courtroom Domain <\/a>\n <\/h3>\n\n
\n Yi Fung, Anoop Kumar, Aram Galstyan, Heng Ji, Prem Natarajan <\/div>\n \n
\n Proceedings of the 2024 Joint International Conference on Computational \u2026<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n q-Diffusion leverages the full dimensionality of gene coexpression in single-cell transcriptomics <\/a>\n <\/h3>\n\n
\n Myrl G Marmarelis, Russell Littman, Francesca Battaglin, Donna Niedzwiecki, Alan Venook, Jose-Luis Ambite, Aram Galstyan, Heinz-Josef Lenz, Greg Ver Steeg <\/div>\n \n
\n Communications Biology 7 (1), 400<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Correcting Language Model Outputs by Editing Salient Layers <\/a>\n <\/h3>\n\n
\n Kshitij Mishra, Tamer Soliman, Anil Ramakrishna, Aram Galstyan, Anoop Kumar <\/div>\n \n
\n Findings of the Association for Computational Linguistics: EACL 2024, 1295-1305<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Prompt perturbation consistency learning for robust language models <\/a>\n <\/h3>\n\n
\n Yao Qiang, Subhrangshu Nandi, Ninareh Mehrabi, Greg Ver Steeg, Anoop Kumar, Anna Rumshisky, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2402.15833<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Synthetic data generation for machine learning models <\/a>\n <\/h3>\n\n
\n R Gupta, N Mehrabi, P Goyal, K Chang, A Galstyan <\/div>\n \n
\n US Patent App. 18\/216,271<\/i>, 2024\n\n <\/div>\n\n <\/div>\n\n \n
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\n \n Learning Morphisms with Gauss-Newton Approximation for Growing Networks <\/a>\n <\/h3>\n\n
\n Neal Lawton, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n arXiv preprint arXiv:2411.05855<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n QuAILoRA: Quantization-Aware Initialization for LoRA <\/a>\n <\/h3>\n\n
\n Neal Lawton, Aishwarya Padmakumar, Judith Gaspers, Jack FitzGerald, Anoop Kumar, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2410.14713<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification <\/a>\n <\/h3>\n\n
\n Tao Meng, Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Aram Galstyan, Richard Zemel, Kai-Wei Chang, Rahul Gupta, Charith Peris <\/div>\n \n
\n arXiv preprint arXiv:2410.05559<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Data advisor: Dynamic data curation for safety alignment of large language models <\/a>\n <\/h3>\n\n
\n Fei Wang, Ninareh Mehrabi, Palash Goyal, Rahul Gupta, Kai-Wei Chang, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2410.05269<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Adaptive Video Understanding Agent: Enhancing efficiency with dynamic frame sampling and feedback-driven reasoning <\/a>\n <\/h3>\n\n
\n Sullam Jeoung, Goeric Huybrechts, Bhavana Ganesh, Aram Galstyan, Sravan Bodapati <\/div>\n \n
\n arXiv preprint arXiv:2410.20252<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n The amazon nova family of models: Technical report and model card <\/a>\n <\/h3>\n\n
\n Amazon Artificial General Intelligence <\/div>\n \n
\n 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2023<\/h2>\n \n
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\n \n Flirt: Feedback loop in-context red teaming <\/a>\n <\/h3>\n\n
\n Ninareh Mehrabi, Palash Goyal, Christophe Dupuy, Qian Hu, Shalini Ghosh, Richard Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta <\/div>\n \n
\n arXiv preprint arXiv:2308.04265<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Partial identification of dose responses with hidden confounders <\/a>\n <\/h3>\n\n
\n Myrl G Marmarelis, Elizabeth Haddad, Andrew Jesson, Neda Jahanshad, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n Uncertainty in Artificial Intelligence, 1368-1379<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs <\/a>\n <\/h3>\n\n
\n Abishek Komma, Nagesh Panyam Chandrasekarasastry, Timothy Leffel, Anuj Goyal, Angeliki Metallinou, Spyros Matsoukas, Aram Galstyan <\/div>\n \n
\n The 61st Annual Meeting Of The Association For Computational Linguistics \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Resolving ambiguities in text-to-image generative models <\/a>\n <\/h3>\n\n
\n Ninareh Mehrabi, Palash Goyal, Apurv Verma, Jwala Dhamala, Varun Kumar, Qian Hu, Kai-Wei Chang, Richard Zemel, Aram Galstyan, Rahul Gupta <\/div>\n \n
\n Proceedings of the 61st Annual Meeting of the Association for Computational \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Multi-task knowledge enhancement for zero-shot and multi-domain recommendation in an AI assistant application <\/a>\n <\/h3>\n\n
\n Elan Markowitz, Ziyan Jiang, Fan Yang, Xing Fan, Tony Chen, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2306.06302<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n \u201cI\u2019m fully who I am\u201d: Towards centering transgender and non-binary voices to measure biases in open language generation <\/a>\n <\/h3>\n\n
\n Anaelia Ovalle, Palash Goyal, Jwala Dhamala, Zachary Jaggers, Kai-Wei Chang, Aram Galstyan, Richard Zemel, Rahul Gupta <\/div>\n \n
\n Proceedings of the 2023 ACM Conference on Fairness, Accountability, and \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning <\/a>\n <\/h3>\n\n
\n Umang Gupta, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n Findings of the Association for Computational Linguistics: ACL 2023<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n History Repeats: Overcoming Catastrophic Forgetting For Event-Centric Temporal Knowledge Graph Completion <\/a>\n <\/h3>\n\n
\n Mehrnoosh Mirtaheri, Mohammad Rostami, Aram Galstyan <\/div>\n \n
\n Findings of the Association for Computational Linguistics: ACL 2023<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n ParaAMR: A large-scale syntactically diverse paraphrase dataset by AMR back-translation <\/a>\n <\/h3>\n\n
\n Kuan-Hao Huang, Varun Iyer, I Hsu, Anoop Kumar, Kai-Wei Chang, Aram Galstyan <\/div>\n \n
\n Proceedings of the 61st Annual Meeting of the Association for Computational \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models <\/a>\n <\/h3>\n\n
\n Neal Lawton, Anoop Kumar, Govind Thattai, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n Findings of the Association for Computational Linguistics: ACL 2023<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Graph meets LLM: A novel approach to collaborative filtering for robust conversational understanding <\/a>\n <\/h3>\n\n
\n Zheng Chen, Ziyan Jiang, Fan Yang, Eunah Cho, Xing Fan, Xiaojiang Huang, Yanbin Lu, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2305.14449<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Measuring and mitigating local instability in deep neural networks <\/a>\n <\/h3>\n\n
\n Arghya Datta, Subhrangshu Nandi, Jingcheng Xu, Greg Ver Steeg, He Xie, Anoop Kumar, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2305.10625<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n ACCENT: An Automatic Event Commonsense Evaluation Metric for Open-Domain Dialogue Systems <\/a>\n <\/h3>\n\n
\n Sarik Ghazarian, Yijia Shao, Rujun Han, Aram Galstyan, Nanyun Peng <\/div>\n \n
\n Proceedings of the 61st Annual Meeting of the Association for Computational \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
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\n \n Incorporating Fairness in Large Scale NLU Systems <\/a>\n <\/h3>\n\n
\n Rahul Gupta, Lisa Bauer, Kai-Wei Chang, Jwala Dhamala, Aram Galstyan, Palash Goyal, Qian Hu, Avni Khatri, Rohit Parimi, Charith Peris, Apurv Verma, Richard Zemel, Prem Natarajan <\/div>\n \n
\n Proceedings of the Sixteenth ACM International Conference on Web Search and \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Overcoming Concept Shift in Domain-Aware Settings through Consolidated Internal Distributions <\/a>\n <\/h3>\n\n
\n Mohammad Rostami, Aram Galstyan <\/div>\n \n
\n Thirty-Seventh AAAI Conference on Artificial Intelligence<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2024<\/h2>\n \n
\n

\n \n Tokenization matters: Navigating data-scarce tokenization for gender inclusive language technologies <\/a>\n <\/h3>\n\n
\n Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal, Jwala Dhamala, Kai-Wei Chang, Richard Zemel, Aram Galstyan, Yuval Pinter, Rahul Gupta <\/div>\n \n
\n Findings of the Association for Computational Linguistics: NAACL 2024, 1739-1756<\/i>, 2024\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2023<\/h2>\n \n
\n

\n \n On the steerability of large language models toward data-driven personas <\/a>\n <\/h3>\n\n
\n Junyi Li, Ninareh Mehrabi, Charith Peris, Palash Goyal, Kai-Wei Chang, Aram Galstyan, Richard Zemel, Rahul Gupta <\/div>\n \n
\n NAACL'24<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Jab: Joint adversarial prompting and belief augmentation <\/a>\n <\/h3>\n\n
\n Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Jwala Dhamala, Shalini Ghosh, Richard Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta <\/div>\n \n
\n arXiv preprint arXiv:2311.09473<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n The first workshop on personalized generative ai@ cikm 2023: Personalization meets large language models <\/a>\n <\/h3>\n\n
\n Zheng Chen, Ziyan Jiang, Fan Yang, Zhankui He, Yupeng Hou, Eunah Cho, Julian McAuley, Aram Galstyan, Xiaohua Hu, Jie Yang <\/div>\n \n
\n Proceedings of the 32nd ACM International Conference on Information and \u2026<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Causal Sensitivity Analysis for Hidden Confounding: Modeling the Sex-Specific Role of Diet on the Aging Brain <\/a>\n <\/h3>\n\n
\n Elizabeth Haddad, Myrl G Marmarelis, Talia M Nir, Aram Galstyan, Greg Ver Steeg, Neda Jahanshad <\/div>\n \n
\n International Workshop on Machine Learning in Clinical Neuroimaging, 91-101<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n An analysis of the effects of decoding algorithms on fairness in open-ended language generation <\/a>\n <\/h3>\n\n
\n Jwala Dhamala, Varun Kumar, Rahul Gupta, Kai-Wei Chang, Aram Galstyan <\/div>\n \n
\n 2022 IEEE Spoken Language Technology Workshop (SLT), 655-662<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Are you talking to [\u2018xem\u2019] or [\u2018x\u2019,\u2018em\u2019]? On tokenization and addressing misgendering in LLMs with pronoun tokenization parity <\/a>\n <\/h3>\n\n
\n Anaelia Ovalle, Ninareh Mehrabi, Palash Goyal, Jwala Dhamala, Kai-Wei Chang, Richard Zemel, Aram Galstyan, Yuval Pinter, Rahul Gupta <\/div>\n \n
\n arXiv preprint arXiv:2312.11779<\/i>, 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Online continual learning for progressive distribution shift (OCL-PDS): A practitioner\u2019s perspective <\/a>\n <\/h3>\n\n
\n Runtian Zhai, Stefan Schroedl, Aram Galstyan, Anoop Kumar, Greg Ver Steeg, Pradeep Natarajan <\/div>\n \n
\n 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Zero-shot cross-lingual sequence tagging as Seq2Seq generation for joint intent classification and slot filling <\/a>\n <\/h3>\n\n
\n Fei Wang, Kuan-Hao Huang, Anoop Kumar, Aram Galstyan, Greg Ver Steeg, Kai-Wei Chang <\/div>\n \n
\n 2023\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2022<\/h2>\n \n
\n

\n \n Temporal generalization for spoken language understanding <\/a>\n <\/h3>\n\n
\n Judith Gaspers, Anoop Kumar, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Proceedings of the 2022 Conference of the North American Chapter of the \u2026<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Proceedings of the 2nd Workshop on Trustworthy Natural Language Processing (TrustNLP 2022) <\/a>\n <\/h3>\n\n
\n Apurv Verma, Yada Pruksachatkun, Kai-Wei Chang, Aram Galstyan, Jwala Dhamala, Yang Trista Cao <\/div>\n \n
\n Proceedings of the 2nd Workshop on Trustworthy Natural Language Processing \u2026<\/i>, 2022\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A metric space for point process excitations <\/a>\n <\/h3>\n\n
\n Myrl G Marmarelis, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Journal of Artificial Intelligence Research 73, 1323\u20131353-1323\u20131353<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n On the intrinsic and extrinsic fairness evaluation metrics for contextualized language representations <\/a>\n <\/h3>\n\n
\n Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, Rahul Gupta, Varun Kumar, Jwala Dhamala, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2203.13928<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Mitigating gender bias in distilled language models via counterfactual role reversal <\/a>\n <\/h3>\n\n
\n Umang Gupta, Jwala Dhamala, Varun Kumar, Apurv Verma, Yada Pruksachatkun, Satyapriya Krishna, Rahul Gupta, Kai-Wei Chang, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2203.12574<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n DEAM: Dialogue Coherence Evaluation using AMR-based Semantic Manipulations <\/a>\n <\/h3>\n\n
\n Sarik Ghazarian, Nuan Wen, Aram Galstyan, Nanyun Peng <\/div>\n \n
\n ACL 2022<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Unsupervised syntactically controlled paraphrase generation with Abstract Meaning Representations <\/a>\n <\/h3>\n\n
\n Kuan-Hao Huang, Varun Iyer, Anoop Kumar, Sriram Venkatapathy, Kai-Wei Chang, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2211.00881<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Formal limitations of sample-wise information-theoretic generalization bounds <\/a>\n <\/h3>\n\n
\n Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n 2022 IEEE Information Theory Workshop (ITW), 440-445<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Identifying geopolitical event precursors using attention-based LSTMs <\/a>\n <\/h3>\n\n
\n KSM Tozammel Hossain, Hrayr Harutyunyan, Yue Ning, Brendan Kennedy, Naren Ramakrishnan, Aram Galstyan <\/div>\n \n
\n Frontiers in Artificial Intelligence 5, 893875<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Learning under label noise for robust spoken language understanding systems <\/a>\n <\/h3>\n\n
\n Anoop Kumar, Pankaj Sharma, Aravind Illa, Sriram Venkatapathy, Subhrangshu Nandi, Pritam Varma, Anurag Dwarakanath, Aram Galstyan <\/div>\n \n
\n 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Failure modes of domain generalization algorithms <\/a>\n <\/h3>\n\n
\n Tigran Galstyan, Hrayr Harutyunyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern \u2026<\/i>, 2022\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2021<\/h2>\n \n
\n

\n \n Plot-guided Adversarial Example Construction for Evaluating Open-domain Story Generation <\/a>\n <\/h3>\n\n
\n Sarik Ghazarian, Zixi Liu, Akash SM, Ralph Weischedel, Aram Galstyan, Nanyun Peng <\/div>\n \n
\n Proceedings of the 2021 Conference of the North American Chapter of the \u2026<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Thirty-Fifth Conference on Neural Information Processing Systems<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Identifying botnet IP address clusters using natural language processing techniques on honeypot command logs <\/a>\n <\/h3>\n\n
\n Valentino Crespi, Wes Hardaker, Sami Abu-El-Haija, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2104.10232<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Influence decompositions for neural network attribution <\/a>\n <\/h3>\n\n
\n Kyle Reing, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n International Conference on Artificial Intelligence and Statistics, 2710-2718<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A survey of human judgement and quantitative forecasting methods <\/a>\n <\/h3>\n\n
\n Maximilian Zellner, Ali E Abbas, David V Budescu, Aram Galstyan <\/div>\n \n
\n Royal Society open science 8 (2), 201187<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Implicit svd for graph representation learning <\/a>\n <\/h3>\n\n
\n Sami Abu-El-Haija, Hesham Mostafa, Marcel Nassar, Valentino Crespi, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Advances in Neural Information Processing Systems 34, 8419-8431<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Information-theoretic generalization bounds for black-box learning algorithms <\/a>\n <\/h3>\n\n
\n Hrayr Harutyunyan, Maxim Raginsky, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Advances in Neural Information Processing Systems 34, 24670-24682<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n q-paths: Generalizing the geometric annealing path using power means <\/a>\n <\/h3>\n\n
\n Vaden Masrani, Rob Brekelmans, Thang Bui, Frank Nielsen, Aram Galstyan, Greg Ver Steeg, Frank Wood <\/div>\n \n
\n Uncertainty in Artificial Intelligence, 1938-1947<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Layer-wise neural network compression via layer fusion <\/a>\n <\/h3>\n\n
\n James O\u2019Neill, Greg V Steeg, Aram Galstyan <\/div>\n \n
\n Asian Conference on Machine Learning, 1381-1396<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Cognitively inspired learning of incremental drifting concepts <\/a>\n <\/h3>\n\n
\n Mohammad Rostami, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2110.04662<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Discovering higher-order interactions through neural information decomposition <\/a>\n <\/h3>\n\n
\n Kyle Reing, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Entropy 23 (1), 79<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Partner-assisted learning for few-shot image classification <\/a>\n <\/h3>\n\n
\n Jiawei Ma, Hanchen Xie, Guangxing Han, Shih-Fu Chang, Aram Galstyan, Wael Abd-Almageed <\/div>\n \n
\n Proceedings of the IEEE\/CVF International Conference on Computer Vision \u2026<\/i>, 2021\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2020<\/h2>\n \n
\n

\n \n Explore more <\/a>\n <\/h3>\n\n
\n Dane Thomas, Daksha Yadav, Tom Jin, Oshry Ben-Harush, Joe Standerfer, Jing Wu, Suiyao Chen, Inseok Heo, Sasha Gutfraind, Shengjie Liu, Chen Li, Bharathi Srinivasan, Xian Zhang, Michael Sharps, Yifan Yang, Kai Zhen, Bhavana Ganesh, Aram Galstyan, Goeric Huybrechts, Markus Mu\u0308ller, Jonas M Ku\u0308bler, Rupak Vignesh Swaminathan, Thanasis Mouchtaris, Sravan Babu Bodapati, Nathan Susanj, Zheng Zhang, Jack GM FitzGerald, Abhishek Kumar <\/div>\n \n
\n Context<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Stacking models for nearly optimal link prediction in complex networks <\/a>\n <\/h3>\n\n
\n Amir Ghasemian, Homa Hosseinmardi, Aram Galstyan, Edoardo M Airoldi, Aaron Clauset <\/div>\n \n
\n Proceedings of the National Academy of Sciences 117 (38), 23393-23400<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Robust classification under class-dependent domain shift <\/a>\n <\/h3>\n\n
\n Tigran Galstyan, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:2007.05335<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n All in the exponential family: Bregman duality in thermodynamic variational inference <\/a>\n <\/h3>\n\n
\n Rob Brekelmans, Vaden Masrani, Frank Wood, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n ICML 2020<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Forecasting violent events in the middle east and north africa using the hidden markov model and regularized autoregressive models <\/a>\n <\/h3>\n\n
\n KSM Tozammel Hossain, Shuyang Gao, Brendan Kennedy, Aram Galstyan, Prem Natarajan <\/div>\n \n
\n The Journal of Defense Modeling and Simulation 17 (3), 269-283<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Modeling dialogues with hashcode representations: A nonparametric approach <\/a>\n <\/h3>\n\n
\n Sahil Garg, Irina Rish, Guillermo Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3970-3979<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Predictive engagement: An efficient metric for automatic evaluation of open-domain dialogue systems <\/a>\n <\/h3>\n\n
\n Sarik Ghazarian, Ralph Weischedel, Aram Galstyan, Nanyun Peng <\/div>\n \n
\n Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 7789-7796<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Likelihood ratio exponential families <\/a>\n <\/h3>\n\n
\n Rob Brekelmans, Frank Nielsen, Alireza Makhzani, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n arXiv preprint arXiv:2012.15480<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Improving generalization by controlling label-noise information in neural network weights <\/a>\n <\/h3>\n\n
\n Hrayr Harutyunyan, Kyle Reing, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n International Conference on Machine Learning, 4071-4081<\/i>, 2020\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2019<\/h2>\n \n
\n

\n \n Deep structured neural network for event temporal relation extraction <\/a>\n <\/h3>\n\n
\n Rujun Han, I Hsu, Mu Yang, Aram Galstyan, Ralph Weischedel, Nanyun Peng <\/div>\n \n
\n arXiv preprint arXiv:1909.10094<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n BioRelEx 1.0: Biological relation extraction benchmark <\/a>\n <\/h3>\n\n
\n Hrant Khachatrian, Lilit Nersisyan, Karen Hambardzumyan, Tigran Galstyan, Anna Hakobyan, Arsen Arakelyan, Andrey Rzhetsky, Aram Galstyan <\/div>\n \n
\n Proceedings of the 18th BioNLP Workshop and Shared Task, 176-190<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Kernelized hashcode representations for relation extraction <\/a>\n <\/h3>\n\n
\n Sahil Garg, Aram Galstyan, Greg Ver Steeg, Irina Rish, Guillermo Cecchi, Shuyang Gao <\/div>\n \n
\n Proceedings of the AAAI conference on artificial intelligence 33 (01), 6431-6440<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Multitask learning and benchmarking with clinical time series data <\/a>\n <\/h3>\n\n
\n Hrayr Harutyunyan, Hrant Khachatrian, David C Kale, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Scientific data 6 (1), 96<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Coupled clustering of time-series and networks <\/a>\n <\/h3>\n\n
\n Yike Liu, Linhong Zhu, Pedro Szekely, Aram Galstyan, Danai Koutra <\/div>\n \n
\n Proceedings of the 2019 SIAM International Conference on Data Mining, 531-539<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Efficient covariance estimation from temporal data <\/a>\n <\/h3>\n\n
\n Hrayr Harutyunyan, Daniel Moyer, Hrant Khachatrian, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1905.13276<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Better automatic evaluation of open-domain dialogue systems with contextualized embeddings <\/a>\n <\/h3>\n\n
\n Sarik Ghazarian, Johnny Tian-Zheng Wei, Aram Galstyan, Nanyun Peng <\/div>\n \n
\n arXiv preprint arXiv:1904.10635<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Auto-encoding total correlation explanation <\/a>\n <\/h3>\n\n
\n Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n The 22nd international conference on artificial intelligence and statistics \u2026<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Maximizing multivariate information with error-correcting codes <\/a>\n <\/h3>\n\n
\n Kyle Reing, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n IEEE Transactions on Information Theory 66 (5), 2683-2695<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Nearly-unsupervised hashcode representations for biomedical relation extraction <\/a>\n <\/h3>\n\n
\n Sahil Garg, Aram Galstyan, Greg Ver Steeg, Guillermo A Cecchi <\/div>\n \n
\n Proceedings of the 2019 conference on empirical methods in natural language \u2026<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Fast structure learning with modular regularization <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Hrayr Harutyunyan, Daniel Moyer, Aram Galstyan <\/div>\n \n
\n Advances in Neural Information Processing Systems 32<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Exact rate-distortion in autoencoders via echo noise <\/a>\n <\/h3>\n\n
\n Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n Advances in neural information processing systems 32<\/i>, 2019\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2018<\/h2>\n \n
\n

\n \n Dialogue modeling via hash functions <\/a>\n <\/h3>\n\n
\n Sahil Garg, Guillermo Cecchi, Irina Rish, Shuyang Gao, Greg Ver Steeg, Sarik Ghazarian, Palash Goyal, Aram Galstyan <\/div>\n \n
\n Linguistic and Cognitive Approaches To Dialog Agents Workshop<\/i>, 2018\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Invariant representations without adversarial training <\/a>\n <\/h3>\n\n
\n Daniel Moyer, Shuyang Gao, Rob Brekelmans, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Advances in Neural Information Processing Systems (NeurIPS)<\/i>, 2018\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A Forest Mixture Bound for Block-Free Parallel Inference <\/a>\n <\/h3>\n\n
\n Neal Lawton, Aram Galstyan, Greg Ver Steeg <\/div>\n \n
\n Uncertainty in Artificial Intelligence (UAI)<\/i>, 2018\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Modeling psychotherapy dialogues with kernelized hashcode representations: A nonparametric information-theoretic approach <\/a>\n <\/h3>\n\n
\n Sahil Garg, Irina Rish, Guillermo Cecchi, Palash Goyal, Sarik Ghazarian, Shuyang Gao, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1804.10188<\/i>, 2018\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Adaptive decision making via entropy minimization <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, Aram Galstyan, Ali E Abbas, Zbigniew R Struzik <\/div>\n \n
\n International Journal of Approximate Reasoning 103, 270-287<\/i>, 2018\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Uncovering biologically coherent peripheral signatures of health and risk for Alzheimer\u2019s disease in the aging brain <\/a>\n <\/h3>\n\n
\n Brandalyn C Riedel, Madelaine Daianu, Greg Ver Steeg, Adam Mezher, Lauren E Salminen, Aram Galstyan, Paul M Thompson, Alzheimer\u2019s Disease Neuroimaging Initiative <\/div>\n \n
\n Frontiers in aging neuroscience 10, 390<\/i>, 2018\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Stochastic learning of nonstationary kernels for natural language modeling <\/a>\n <\/h3>\n\n
\n Sahil Garg, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1801.03911<\/i>, 2018\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Sensemaking Research Roadmap <\/a>\n <\/h3>\n\n
\n KP Subbalakshmi, Aram Galstyan, Rama Chellappa, Charles Clancy <\/div>\n \n
\n Stevens Institute of Technology Hoboken<\/i>, 2018\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Highly accurate link prediction in networks using stacked generalization <\/a>\n <\/h3>\n\n
\n Amir Ghasemian, AG Galstyan, Aaron Clauset <\/div>\n \n
\n WSDM<\/i>, 2018\n\n <\/div>\n\n <\/div>\n\n

2017<\/h2>\n \n
\n

\n \n Sifting Common Information from Many Variables. <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan <\/div>\n \n
\n IJCAI, 2885-2892<\/i>, 2017\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Unifying Local and Global Change Detection in Dynamic Networks <\/a>\n <\/h3>\n\n
\n Wenzhe Li, Dong Guo, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1710.03035<\/i>, 2017\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Disentangled representations via synergy minimization <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Rob Brekelmans, Hrayr Harutyunyan, Aram Galstyan <\/div>\n \n
\n 2017 55th Annual Allerton Conference on Communication, Control, and \u2026<\/i>, 2017\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2016<\/h2>\n \n
\n

\n \n Situational Awareness for Social Media: Theories, Models and Algorithms <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Kristina Lerman, Eduard Hovy, Yan Liu, Ram Nevatia <\/div>\n \n
\n 2016\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Emergence of leadership in communication <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, Aram Galstyan <\/div>\n \n
\n PloS one 11 (8), e0159301<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Scalable temporal latent space inference for link prediction in dynamic social networks <\/a>\n <\/h3>\n\n
\n Linhong Zhu, Dong Guo, Junming Yin, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n IEEE Transactions on Knowledge and Data Engineering 28 (10), 2765-2777<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Sifting common information from many variables <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Shuyang Gao, Kyle Reing, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1606.02307<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Toward interpretable topic discovery via anchored correlation explanation <\/a>\n <\/h3>\n\n
\n Kyle Reing, David C Kale, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1606.07043<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n The DARPA Twitter bot challenge <\/a>\n <\/h3>\n\n
\n Venkatramanan S Subrahmanian, Amos Azaria, Skylar Durst, Vadim Kagan, Aram Galstyan, Kristina Lerman, Linhong Zhu, Emilio Ferrara, Alessandro Flammini, Filippo Menczer <\/div>\n \n
\n Computer 49 (6), 38-46<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n The information sieve <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n International Conference on Machine Learning, 164-172<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Using social media, online social networks, and internet search as platforms for public health interventions: a pilot study <\/a>\n <\/h3>\n\n
\n Marco D Huesch, Aram Galstyan, Michael K Ong, Jason N Doctor <\/div>\n \n
\n Health services research 51, 1273-1290<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Latent space model for multi-modal social data <\/a>\n <\/h3>\n\n
\n Yoon-Sik Cho, Greg Ver Steeg, Emilio Ferrara, Aram Galstyan <\/div>\n \n
\n Proceedings of the 25th international conference on world wide web, 447-458<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Extracting biomolecular interactions using semantic parsing of biomedical text <\/a>\n <\/h3>\n\n
\n Sahil Garg, Aram Galstyan, Ulf Hermjakob, Daniel Marcu <\/div>\n \n
\n Proceedings of the AAAI Conference on Artificial Intelligence 30 (1)<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Relative value of diverse brain MRI and blood-based biomarkers for predicting cognitive decline in the elderly <\/a>\n <\/h3>\n\n
\n Sarah K Madsen, Greg Ver Steeg, Madelaine Daianu, Adam Mezher, Neda Jahanshad, Talia M Nir, Xue Hua, Boris A Gutman, Aram Galstyan, Paul M Thompson <\/div>\n \n
\n Medical Imaging 2016: Image Processing 9784, 281-286<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Inferring Structure and Forecasting Dynamics on Evolving Networks <\/a>\n <\/h3>\n\n
\n Jeffrey P Brantingham, Ronald Breiger, Yu-han Chang, Aram Galstyan, Kristina Lerman, Michael Mcbride, Igor Mezic, Brinton Milward, Clayton Morrison, Allon Percus, George E Tita, Andrea L Bertozzi <\/div>\n \n
\n 2016\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Variational information maximization for feature selection <\/a>\n <\/h3>\n\n
\n Shuyang Gao, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Advances in neural information processing systems 29<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Unsupervised entity resolution on multi-type graphs <\/a>\n <\/h3>\n\n
\n Linhong Zhu, Majid Ghasemi-Gol, Pedro Szekely, Aram Galstyan, Craig A Knoblock <\/div>\n \n
\n The Semantic Web\u2013ISWC 2016: 15th International Semantic Web Conference, Kobe \u2026<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Information-theoretic clustering of neuroimaging metrics related to cognitive decline in the elderly <\/a>\n <\/h3>\n\n
\n Madelaine Daianu, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M Nir, Xiaoran Yan, Gautam Prasad, Kristina Lerman, Aram Galstyan, Paul M Thompson <\/div>\n \n
\n Medical Computer Vision: Algorithms for Big Data: International Workshop \u2026<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Modeling Concept Dependencies in a Scientific Corpus <\/a>\n <\/h3>\n\n
\n Jonathan Gordon, Linhong Zhu, Aram Galstyan, Prem Natarajan, Gully Burns <\/div>\n \n
\n Proc. of the Association for Computational Linguistics (ACL)<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Predicting online extremism, content adopters, and interaction reciprocity <\/a>\n <\/h3>\n\n
\n Emilio Ferrara, Wen-Qiang Wang, Onur Varol, Alessandro Flammini, Aram Galstyan <\/div>\n \n
\n Social Informatics: 8th International Conference, SocInfo 2016, Bellevue, WA \u2026<\/i>, 2016\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2015<\/h2>\n \n
\n

\n \n Estimating mutual information by local Gaussian approximation <\/a>\n <\/h3>\n\n
\n Shuyang Gao, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Uncertianty in Artificial Intelligence (UAI)<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Outreach Using Social Media Campaigns: Micro-Education for $1 per Patient <\/a>\n <\/h3>\n\n
\n Marco Huesch, Jason Doctor, Aram Galstyan <\/div>\n \n
\n 2015 Annual Research Meeting<\/i>, 2015\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Using Online Social Media and Social Networks as a Public Health Intervention <\/a>\n <\/h3>\n\n
\n Marco Huesch, Jason N Doctor, Aram Galstyan <\/div>\n \n
\n CESR-Schaeffer Working Paper<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Learning bounded rationality models of the adversary in repeated Stackelberg Security Games <\/a>\n <\/h3>\n\n
\n Debarun Kar, Fei Fang, Francesco Delle Fave, Nicole Sintov, Arunesh Sinha, Aram Galstyan, Bo An, Milind Tambe <\/div>\n \n
\n Retrieved from Nanyang Technological University: http:\/\/www3. ntu. edu. sg \u2026<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Predicting Cognitive Decline with Information-Theoretic Clustering of Brain MRI and Blood Tests <\/a>\n <\/h3>\n\n
\n Sarah K Madsen, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M Nir, Xue Hua, Boris A Gutman, Aram Galstyan, Paul M Thompson <\/div>\n \n
\n BIOLOGICAL PSYCHIATRY 77 (9), 96S-96S<\/i>, 2015\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Information-theoretic characterization of blood panel predictors for brain atrophy and cognitive decline in the elderly <\/a>\n <\/h3>\n\n
\n Sarah K Madsen, Greg Ver Steeg, Adam Mezher, Neda Jahanshad, Talia M Nir, Xue Hua, Boris A Gutman, Aram Galstyan, Paul M Thompson <\/div>\n \n
\n 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 980-984<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Efficient estimation of mutual information for strongly dependent variables <\/a>\n <\/h3>\n\n
\n Shuyang Gao, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Artificial intelligence and statistics, 277-286<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Memory-induced mechanism for self-sustaining activity in networks <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, G Ver Steeg, Aram Galstyan <\/div>\n \n
\n Physical Review E 92 (6), 062824<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Active inference for binary symmetric hidden Markov models <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, Aram Galstyan <\/div>\n \n
\n Journal of Statistical Physics 161, 452-466<\/i>, 2015\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2014<\/h2>\n \n
\n

\n \n Opinion dynamics with confirmation bias <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, Aram Galstyan <\/div>\n \n
\n PloS one 9 (7), e99557<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Where and why users \u201ccheck in\u201d <\/a>\n <\/h3>\n\n
\n Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Proc. of AAAI 14, 269-275<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Tripartite graph clustering for dynamic sentiment analysis on social media <\/a>\n <\/h3>\n\n
\n Linhong Zhu, Aram Galstyan, James Cheng, Kristina Lerman <\/div>\n \n
\n Proceedings of the 2014 ACM SIGMOD international conference on Management of \u2026<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Phase transitions in community detection: A solvable toy model <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Cristopher Moore, Aram Galstyan, Armen Allahverdyan <\/div>\n \n
\n Europhysics Letters 106 (4), 48004<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Modeling temporal activity patterns in dynamic social networks <\/a>\n <\/h3>\n\n
\n Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G Tartakovsky <\/div>\n \n
\n IEEE Transactions on Computational Social Systems 1 (1), 89-107<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Understanding confounding effects in linguistic coordination: an information-theoretic approach <\/a>\n <\/h3>\n\n
\n Shuyang Gao, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1412.0696<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Mixed Membership Blockmodels for Dynamic Networks with Feedback. <\/a>\n <\/h3>\n\n
\n Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Handbook of mixed membership models and their applications, 527-545<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Maximally Informative Hierarchical Representations of High-Dimensional Data <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Artificial Intelligence and Statistics (AISTATS)<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Discovering structure in high-dimensional data through correlation explanation <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Advances in Neural Information Processing Systems 27<\/i>, 2014\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2013<\/h2>\n \n
\n

\n \n Socially relevant venue clustering from check-in data <\/a>\n <\/h3>\n\n
\n Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n KDD Workshop on Mining and Learning with Graphs<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Coupled hidden markov models for user activity in social networks <\/a>\n <\/h3>\n\n
\n Vasanthan Raghavan, Greg Ver Steeg, Aram Galstyan, Alexander G Tartakovsky <\/div>\n \n
\n 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 1-6<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Vaccination (anti-) campaigns in social media <\/a>\n <\/h3>\n\n
\n Marco Huesch, Greg Ver-Steeg, Aram Galstyan <\/div>\n \n
\n Workshops at the twenty-seventh AAAI conference on artificial intelligence<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Coevolutionary networks of reinforcement-learning agents <\/a>\n <\/h3>\n\n
\n Ardeshir Kianercy, Aram Galstyan <\/div>\n \n
\n Physical Review E\u2014Statistical, Nonlinear, and Soft Matter Physics 88 (1 \u2026<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Latent self-exciting point process model for spatial-temporal networks <\/a>\n <\/h3>\n\n
\n Yoon-Sik Cho, Aram Galstyan, P Jeffrey Brantingham, George Tita <\/div>\n \n
\n arXiv preprint arXiv:1302.2671<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Hidden Markov models for the activity profile of terrorist groups <\/a>\n <\/h3>\n\n
\n Vasanthan Raghavan, Aram Galstyan, Alexander G Tartakovsky <\/div>\n \n
\n The Annals of Applied Statistics, 2402-2430<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Activation Cascades in Structured Populations <\/a>\n <\/h3>\n\n
\n Aram Galstyan <\/div>\n \n
\n Handbook of Human Computation, 779-789<\/i>, 2013\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Demystifying information-theoretic clustering <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan, Fei Sha, Simon DeDeo <\/div>\n \n
\n ICML<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Continuous strategy replicator dynamics for multi-agent q-learning <\/a>\n <\/h3>\n\n
\n Aram Galstyan <\/div>\n \n
\n Autonomous agents and multi-agent systems 26, 37-53<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Sentiment prediction using collaborative filtering <\/a>\n <\/h3>\n\n
\n Jihie Kim, Jaebong Yoo, Ho Lim, Huida Qiu, Zornitsa Kozareva, Aram Galstyan <\/div>\n \n
\n Proceedings of the International AAAI Conference on Web and Social Media 7 \u2026<\/i>, 2013\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2012<\/h2>\n \n
\n

\n \n Information-Theoretic Measures of Influence Based on Content Dynamics <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n WSDM 2013<\/i>, 2012\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Adaptive agents on evolving networks. <\/a>\n <\/h3>\n\n
\n Ardeshir Kianercy, Aram Galstyan, Armen E Allahverdyan <\/div>\n \n
\n AAMAS, 1391-1392<\/i>, 2012\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Dynamics of Boltzmann learning in two-player two-action games <\/a>\n <\/h3>\n\n
\n Ardeshir Kianercy, Aram Galstyan <\/div>\n \n
\n Physical Review E\u2014Statistical, Nonlinear, and Soft Matter Physics 85 (4 \u2026<\/i>, 2012\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Statistical tests for contagion in observational social network studies <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1211.4889<\/i>, 2012\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Generative models for spatial-temporal processes with applications to predictive criminology <\/a>\n <\/h3>\n\n
\n Y Cho, Aram Galstyan, Jeff Brantingham, George Tita <\/div>\n \n
\n 2012\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2011<\/h2>\n \n
\n

\n \n Statistical mechanics of semi-supervised clustering in sparse graphs <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan, Armen E Allahverdyan <\/div>\n \n
\n Journal of Statistical Mechanics: Theory and Experiment 2011 (08), P08009<\/i>, 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Co-evolution of selection and influence in social networks <\/a>\n <\/h3>\n\n
\n Yoon-Sik Cho, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:1106.2788<\/i>, 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A Sequence of Relaxations Constraining Hidden Variable Models <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Le Chatelier's principle in replicator dynamics <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, Aram Galstyan <\/div>\n \n
\n Physical Review E\u2014Statistical, Nonlinear, and Soft Matter Physics 84 (4 \u2026<\/i>, 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Information Transfer in Social Media <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n WWW 2012<\/i>, 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Comparative Analysis of Viterbi Training and Maximum Likelihood Estimation for HMMs <\/a>\n <\/h3>\n\n
\n Armen Allahverdyan, Aram Galstyan <\/div>\n \n
\n Neural Information Processing Systems (NIPS).<\/i>, 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2010<\/h2>\n \n
\n

\n \n Towards modeling social and content dynamics in discussion forums <\/a>\n <\/h3>\n\n
\n Jihie Kim, Aram Galstyan <\/div>\n \n
\n Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a \u2026<\/i>, 2010\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Community detection with and without prior information <\/a>\n <\/h3>\n\n
\n Armen E Allahverdyan, Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n Europhysics Letters 90 (1), 18002<\/i>, 2010\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Clustering with Prior Information <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg <\/div>\n \n
\n Relation<\/i>, 2010\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Replicator Dynamics of Coevolving Networks. <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Ardeshir Kianercy, Armen E Allahverdyan <\/div>\n \n
\n 2010 AAAI Fall Symposium Series<\/i>, 2010\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Ruling out latent homophily in social networks <\/a>\n <\/h3>\n\n
\n Greg Ver Steeg, Aram Galstyan <\/div>\n \n
\n NIPSWorkshop on Social Computing<\/i>, 2010\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2009<\/h2>\n \n
\n

\n \n On maximum a posteriori estimation of hidden Markov processes <\/a>\n <\/h3>\n\n
\n Armen Allahverdyan, Aram Galstyan <\/div>\n \n
\n arXiv preprint arXiv:0906.1980<\/i>, 2009\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Maximizing influence propagation in networks with community structure <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Vahe Musoyan, Paul Cohen <\/div>\n \n
\n Physical Review E\u2014Statistical, Nonlinear, and Soft Matter Physics 79 (5 \u2026<\/i>, 2009\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Tentacles: Self-configuring robotic radio networks in unknown environments <\/a>\n <\/h3>\n\n
\n Harris Chi Ho Chiu, Bo Ryu, Hua Zhu, Pedro Szekely, Rajiv Maheswaran, Craig Rogers, Aram Galstyan, Behnam Salemi, Mike Rubenstein, Wei-Min Shen <\/div>\n \n
\n 2009 IEEE\/RSJ International Conference on Intelligent Robots and Systems \u2026<\/i>, 2009\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2008<\/h2>\n \n
\n

\n \n Analysis of social voting patterns on digg <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n Proceedings of the first workshop on Online social networks, 7-12<\/i>, 2008\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Top-down vs bottom-up methodologies in multi-agent system design <\/a>\n <\/h3>\n\n
\n Valentino Crespi, Aram Galstyan, Kristina Lerman <\/div>\n \n
\n Autonomous Robots 24, 303-313<\/i>, 2008\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Comparing Diffusion Models for Graph\u2013Based Semi\u2013Supervised Learning <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n 6th International Workshop on Mining and Learning with Graphs<\/i>, 2008\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Influence Propagation in Modular Networks. <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n AAAI Spring Symposium: Social Information Processing, 21-23<\/i>, 2008\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2007<\/h2>\n \n
\n

\n \n Empirical comparison of \u201chard\u201d and \u201csoft\u201d label propagation for relational classification <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n International Conference on Inductive Logic Programming, 98-111<\/i>, 2007\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Cascading dynamics in modular networks <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul Cohen <\/div>\n \n
\n Physical Review E\u2014Statistical, Nonlinear, and Soft Matter Physics 75 (3 \u2026<\/i>, 2007\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Activity Spreading in Modular Networks <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n 2007\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Detecting and tracking hostile plans in the Hats world <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Sinjini Mitra, Paul Cohen <\/div>\n \n
\n AAAI Workshop on Plan, Activity, and Intent Recognition, PAIR\u201307<\/i>, 2007\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2011<\/h2>\n \n
\n

\n \n 2. REPORT DATE <\/a>\n <\/h3>\n\n
\n A Galstyan, A Bertozzi, P Cohen, G Medioni, C Papadopolous, B Rozovsky, A Tartakovsky, V Veeravalli <\/div>\n \n
\n 2011\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2006<\/h2>\n \n
\n

\n \n Relational classification through three-state epidemic dynamics <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul Cohen <\/div>\n \n
\n 2006 9th International Conference on Information Fusion, 1-7<\/i>, 2006\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Analysis of dynamic task allocation in multi-robot systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Chris Jones, Aram Galstyan, Maja J Matari\u0107 <\/div>\n \n
\n The International Journal of Robotics Research 25 (3), 225-241<\/i>, 2006\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Three-State Epidemic Dynamics <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n Intelligence and Security Informatics:... NSF\/NIJ Symposium, ISI \u2026<\/i>, 2006\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Part I-Long Papers-Intelligence Analysis and Knowledge Discovery-Iterative Relational Classification Through Three-State Epidemic Dynamics <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n Lecture Notes in Computer Science 3975, 83-92<\/i>, 2006\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Iterative relational classification through three\u2013state epidemic dynamics <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n Intelligence and Security Informatics: IEEE International Conference on \u2026<\/i>, 2006\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n The jean system <\/a>\n <\/h3>\n\n
\n Yu-Han Chang, Clayton T Morrison, Wesley Kerr, Aram Galstyan, Paul R Cohen, Carole Beal, Robert St Amant, Tim Oates <\/div>\n \n
\n Proceedings of the Fifth International Conference on Development and \u2026<\/i>, 2006\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2005<\/h2>\n \n
\n

\n \n Inferring Useful Heuristics from the Dynamics of Iterative Relational Classifiers. <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n IJCAI, 708-713<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Comparative analysis of top-down and bottom-up methodologies for multi-agent system design <\/a>\n <\/h3>\n\n
\n Valentino Crespi, Aram Galstyan, Kristina Lerman <\/div>\n \n
\n Proceedings of the fourth international joint conference on Autonomous \u2026<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Modeling and mathematical analysis of swarms of microscopic robots <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Tad Hogg, Kristina Lerman <\/div>\n \n
\n Proceedings 2005 IEEE Swarm Intelligence Symposium. SIS 2005., 201-208<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Resource allocation in the grid with learning agents <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Karl Czajkowski, Kristina Lerman <\/div>\n \n
\n Journal of Grid Computing 3, 91-100<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Population generation for large-scale simulation <\/a>\n <\/h3>\n\n
\n Andrew C Hannon, Gary King, Clayton Morrison, Aram Galstyan, Paul Cohen <\/div>\n \n
\n Enabling Technologies for Simulation Science IX 5805, 116-127<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Mathematical modeling of large multi-agent systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Maja Mataric, Aram Galstyan <\/div>\n \n
\n CALIFORNIA UNIV LOS ANGELES, Tech. Rep<\/i>, 2005\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Identifying covert sub-networks through iterative node classification <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Paul R Cohen <\/div>\n \n
\n Proceedings of the First International Conference on Intelligence Analysis<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A review of probabilistic macroscopic models for swarm robotic systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Alcherio Martinoli, Aram Galstyan <\/div>\n \n
\n Swarm Robotics, 143-152<\/i>, 2005\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2004<\/h2>\n \n
\n

\n \n Analysis of a stochastic model of adaptive task allocation in robots <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Kristina Lerman <\/div>\n \n
\n International Workshop on Engineering Self-Organising Applications, 167-179<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Hormone-inspired self-organization and distributed control of robotic swarms <\/a>\n <\/h3>\n\n
\n Wei-Min Shen, Peter Will, Aram Galstyan, Cheng-Ming Chuong <\/div>\n \n
\n Autonomous Robots 17 (1), 93-105<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Resource allocation and emergent coordination in wireless sensor networks <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Bhaskar Krishnamachari, Kristina Lerman <\/div>\n \n
\n AAAI Workshop on Sensor Networks<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Distributed online localization in sensor networks using a moving target <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Bhaskar Krishnamachari, Kristina Lerman, Sundeep Pattem <\/div>\n \n
\n Proceedings of the 3rd international symposium on Information processing in \u2026<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Mathematical analysis of multi-agent systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan, Tad Hogg <\/div>\n \n
\n arXiv preprint cs\/0404002<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Resource allocation in the grid using reinforcement learning <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Karl Czajkowski, Kristina Lerman <\/div>\n \n
\n Proceedings of the Third International Joint Conference on Autonomous Agents \u2026<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Two paradigms for the design of artificial collectives <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n Collectives and the design of complex systems, 231-256<\/i>, 2004\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Automatically modeling group behavior of simple agents <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n Agent Modeling Workshop, AAMAS-04, New York, NY<\/i>, 2004\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2003<\/h2>\n \n
\n

\n \n Agent memory and adaptation in multi-agent systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n Proceedings of the second international joint conference on Autonomous \u2026<\/i>, 2003\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Resource allocation games with changing resource capacities <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Shashikiran Kolar, Kristina Lerman <\/div>\n \n
\n Proceedings of the second international joint conference on Autonomous \u2026<\/i>, 2003\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Threshold Behavior in a Boolean Network Model for SAT. <\/a>\n <\/h3>\n\n
\n Alejandro Bugacov, Aram Galstyan, Kristina Lerman <\/div>\n \n
\n IC-AI, 87-92<\/i>, 2003\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Macroscopic analysis of adaptive task allocation in robots <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n Proceedings 2003 IEEE\/RSJ International Conference on Intelligent Robots and \u2026<\/i>, 2003\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2002<\/h2>\n \n
\n

\n \n Mathematical model of foraging in a group of robots: Effect of interference <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n Autonomous Robots 13 (2), 127-141<\/i>, 2002\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Adaptive Boolean networks and minority games with time-dependent capacities <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Kristina Lerman <\/div>\n \n
\n Physical Review E 66 (1), 015103<\/i>, 2002\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Minority games and distributed coordination in non-stationary environments <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Kristina Lerman <\/div>\n \n
\n Proceedings of the 2002 International Joint Conference on Neural Networks \u2026<\/i>, 2002\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n PART 2-RAPID COMMUNICATIONS-General methods of statistical physics-Adaptive Boolean networks and minority games with time-dependent capacities <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Kristina Lerman <\/div>\n \n
\n Physical Review-Section E-Statistical Nonlinear and Soft Matter Physics 66 \u2026<\/i>, 2002\n\n <\/div>\n\n <\/div>\n\n

2001<\/h2>\n \n
\n

\n \n A stochastic model of platoon formation in traffic flow <\/a>\n <\/h3>\n\n
\n A Galstyan, K Lerman <\/div>\n \n
\n Proceedings of the TASK workshop, Santa Fe, NM, 17-19<\/i>, 2001\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A macroscopic analytical model of collaboration in distributed robotic systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan, Alcherio Martinoli, Auke Ijspeert <\/div>\n \n
\n Artificial Life 7 (4), 375-393<\/i>, 2001\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Phase-slip induced distributed feedback resonator modes with tilted modulation <\/a>\n <\/h3>\n\n
\n AG Galstyan, ME Raikh, ZV Vardeny <\/div>\n \n
\n Synthetic metals 116 (1-3), 493-496<\/i>, 2001\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Dipole radiation from semi-infinite photonic crystal <\/a>\n <\/h3>\n\n
\n AG Galstyan, ME Raikh, ZV Vardeny <\/div>\n \n
\n Synthetic metals 116 (1-3), 465-467<\/i>, 2001\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n A general methodology for mathematical analysis of multi-agent systems <\/a>\n <\/h3>\n\n
\n Kristina Lerman, Aram Galstyan <\/div>\n \n
\n ISI-TR-529, USC Information Sciences Institute, Marina del Rey, CA<\/i>, 2001\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n

2000<\/h2>\n \n
\n

\n \n Emission spectrum of a dipole in a semi-infinite periodic dielectric structure: effect of the boundary <\/a>\n <\/h3>\n\n
\n AG Galstyan, ME Raikh, ZV Vardeny <\/div>\n \n
\n Physical Review B 62 (3), 1780<\/i>, 2000\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Electronic and photonic states in inhomogeneous media <\/a>\n <\/h3>\n\n
\n Aram Galstyan <\/div>\n \n
\n The University of Utah<\/i>, 2000\n\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Electronic structure: Wide-band, narrow-band, and strongly correlated systems-Emission spectrum of a dipole in a semi-infinite periodic dielectric structure: Effect of the boundary <\/a>\n <\/h3>\n\n
\n AG Galstyan, ME Raikh, ZV Vardeny <\/div>\n \n
\n Physical Review-Section B-Condensed Matter 62 (3), 1780-1786<\/i>, 2000\n\n <\/div>\n\n <\/div>\n\n

1998<\/h2>\n \n
\n

\n \n Disorder-induced broadening of the density of states for two-dimensional electrons with strong spin-orbit coupling <\/a>\n <\/h3>\n\n
\n AG Galstyan, ME Raikh <\/div>\n \n
\n Physical Review B 58 (11), 6736<\/i>, 1998\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n
\n

\n \n Density of States of 2D Electrons with Strong Spin-Orbit Coupling <\/a>\n <\/h3>\n\n
\n Aram Galstyan, Mikhail Raikh <\/div>\n \n
\n APS Four Corners Section Meeting Abstracts, A3. 04<\/i>, 1998\n\n <\/div>\n\n <\/div>\n\n

1997<\/h2>\n \n
\n

\n \n Localization and conductance fluctuations in the integer quantum Hall effect: Real-space renormalization-group approach <\/a>\n <\/h3>\n\n
\n AG Galstyan, ME Raikh <\/div>\n \n
\n Physical Review B 56 (3), 1422<\/i>, 1997\n\n
\n View Paper<\/a>\n <\/div>\n <\/div>\n\n <\/div>\n\n \n <\/div>\n\n \n\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":421,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"news_source":"","news_author":"","external_news_link":"","footnotes":""},"class_list":["post-11","page","type-page","status-publish","hentry"],"yoast_head":"\nPublications - Aram Galstyan<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.isi.edu\/people-galstyan\/publications\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Publications - Aram Galstyan\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.isi.edu\/people-galstyan\/publications\/\" \/>\n<meta property=\"og:site_name\" content=\"Aram Galstyan\" \/>\n<meta property=\"article:modified_time\" content=\"2025-06-13T17:43:35+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/www.isi.edu\\\/people-galstyan\\\/publications\\\/\",\"url\":\"https:\\\/\\\/www.isi.edu\\\/people-galstyan\\\/publications\\\/\",\"name\":\"Publications - 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