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- research-articleOctober 2024Best Paper
Towards Empathetic Conversational Recommender Systems
- Xiaoyu Zhang,
- Ruobing Xie,
- Yougang Lyu,
- Xin Xin,
- Pengjie Ren,
- Mingfei Liang,
- Bo Zhang,
- Zhanhui Kang,
- Maarten de Rijke,
- Zhaochun Ren
RecSys '24: Proceedings of the 18th ACM Conference on Recommender SystemsPages 84–93https://doi.org/10.1145/3640457.3688133Conversational recommender systems (CRSs) are able to elicit user preferences through multi-turn dialogues. They typically incorporate external knowledge and pre-trained language models to capture the dialogue context. Most CRS approaches, trained on ...
- research-articleSeptember 2024
Integrating discourse features and response assessment for advancing empathetic dialogue
Information Processing and Management: an International Journal (IPRM), Volume 61, Issue 5https://doi.org/10.1016/j.ipm.2024.103803AbstractEmpathetic response generation is a crucial task in natural language processing, enabling emotionally resonant machine–human interactions. In this paper, we introduce the InfRa (Integrating Discourse Features and Response Assessment) model to ...
Highlights- Introduce InfRa model for dialogue comprehension and empathetic response generation.
- Optimize feature representation with edge pruning and mutual information learning.
- Employ feedback mechanism for emotional and semantic assessment,...
- research-articleDecember 2021
Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality
AbstractEmpathetic response generation aims to comprehend the user emotion and then respond to it appropriately. Most existing works merely focus on what the emotion is and ignore how the emotion is evoked, thus weakening the capacity of the ...