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CoMAE: A Multi-factor Hierarchical Framework for Empathetic Response Generation

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arxiv 2105.08316 v3 pith:DN42X3Y5 submitted 2021-05-18 cs.CL

classification cs.CL
keywords empathyhierarchicalempatheticfactorscomaegenerationresponsedialog
verification ladder T0 review T1 audit T2 compute T3 formal
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The capacity of empathy is crucial to the success of open-domain dialog systems. Due to its nature of multi-dimensionality, there are various factors that relate to empathy expression, such as communication mechanism, dialog act and emotion. However, existing methods for empathetic response generation usually either consider only one empathy factor or ignore the hierarchical relationships between different factors, leading to a weak ability of empathy modeling. In this paper, we propose a multi-factor hierarchical framework, CoMAE, for empathetic response generation, which models the above three key factors of empathy expression in a hierarchical way. We show experimentally that our CoMAE-based model can generate more empathetic responses than previous methods. We also highlight the importance of hierarchical modeling of different factors through both the empirical analysis on a real-life corpus and the extensive experiments. Our codes and used data are available at https://github.com/chujiezheng/CoMAE.

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  1. EmoAssist: Emotional Assistant for Visual Impairment Community

    cs.CV 2025-02 conditional novelty 6.0 of 10

    A fine-tuned LLaVA model, trained with preference optimization on 800 emotional image-QA examples, beats GPT-4o on a new empathy-focused benchmark for visual impairment assistance.

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