Empathetic Response Generation through Graph-based Multi-hop Reasoning on Emotional Causality
Empathetic 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 model to understand the emotional experience of the user for generating empathetic responses. To tackle this problem, we consider the emotional causality, namely, what feelings the user expresses (i.e., emotion) and why the user has such feelings (i.e., cause). Then, we propose a novel graph-based model with multi-hop reasoning to model the emotional causality of the empathetic conversation. Finally, we demonstrate the effectiveness of our model on EMPATHETICDIALOGUES in comparison with several competitive models.
Code (0)
등록된 구현이 없습니다.
Tasks
Empathetic Response GenerationResponse GenerationSimilar Papers 제목 키워드 기반
CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation
Empathetic conversation is psychologically supposed to be the result of conscious alignment and interaction between the cognition and affection of empathy. However, existing empathetic dialogue models usually consider on…
Dialogue GenerationEmpathetic Response GenerationResponse GenerationExploiting Emotion-Semantic Correlations for Empathetic Response Generation
Empathetic response generation aims to generate empathetic responses by understanding the speaker's emotional feelings from the language of dialogue. Recent methods capture emotional words in the language of communicator…
Dialogue GenerationEmpathetic Response GenerationResponse GenerationE-CORE: Emotion Correlation Enhanced Empathetic Dialogue Generation
Achieving empathy is a crucial step toward humanized dialogue systems. Current approaches for empathetic dialogue generation mainly perceive an emotional label to generate an empathetic response conditioned on it, which …
DecoderDialogue GenerationResponse GenerationCARE: Causality Reasoning for Empathetic Responses by Conditional Graph Generation
Recent approaches to empathetic response generation incorporate emotion causalities to enhance comprehension of both the user's feelings and experiences. However, these approaches suffer from two critical issues. First, …
DecoderEmpathetic Response GenerationGraph GenerationResponse GenerationEmPO: Emotion Grounding for Empathetic Response Generation through Preference Optimization
Empathetic response generation is a desirable aspect of conversational agents, crucial for facilitating engaging and emotionally intelligent multi-turn conversations between humans and machines. Leveraging large language…
DiversityEmpathetic Response GenerationMMLUResponse Generation