Publications

Personalized response generation via generative split memory network

Abstract

Despite the impressive successes of generation and dialogue systems, how to endow a text generation system with particular personality traits to deliver more personalized responses remains under-investigated. In this work, we look at how to generate personalized responses for questions on Reddit by utilizing personalized user profiles and posting histories. Specifically, we release an open-domain single-turn dialog dataset made up of 1.5 M conversation pairs together with 300k profiles of users and related comments. We then propose a memory network to generate personalized responses in dialogue that utilizes a novel mechanism of splitting memories: one for user profile meta attributes and the other for user-generated information like comment histories. Experimental results show the quantitative and qualitative improvements of our simple split memory network model over the state-of-the-art response generation baselines.

Date
2021
Authors
Yuwei Wu, Xuezhe Ma, Diyi Yang
Conference
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Pages
1956-1970