论文标题
案例：对善解人心的反应产生的粗到精美的认知和感情
CASE: Aligning Coarse-to-Fine Cognition and Affection for Empathetic Response Generation
论文作者
论文摘要
在心理上，同情对话应该是同理心认知和感情之间有意识地对齐和相互作用的结果。但是，现有的同理心对话模型通常仅考虑情感方面或孤立地处理认知和感情，这限制了慈善反应产生的能力。在这项工作中，我们提出了同情对话生成的案例模型。它首先建立在常识性认知图和情感概念图上，然后在用粗粒和细粒度的水平上对齐用户的认知和感情。通过自动和手动评估，我们证明了该案例的表现优于善解人意对话的最先进的基准，并且可以产生更多的善解人意和信息丰富的响应。
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 only the affective aspect or treat cognition and affection in isolation, which limits the capability of empathetic response generation. In this work, we propose the CASE model for empathetic dialogue generation. It first builds upon a commonsense cognition graph and an emotional concept graph and then aligns the user's cognition and affection at both the coarse-grained and fine-grained levels. Through automatic and manual evaluation, we demonstrate that CASE outperforms state-of-the-art baselines of empathetic dialogues and can generate more empathetic and informative responses.
