COMPEER: Controllable Empathetic Reinforcement Reasoning for Emotional Support Conversation

• URL: http://arxiv.org/abs/2508.09521v1
• Date: Wed, 13 Aug 2025 06:09:32 GMT
• Title: COMPEER: Controllable Empathetic Reinforcement Reasoning for Emotional Support Conversation
• Authors: Yunxiao Wang, Meng Liu, Wenqi Liu, Kaiyu Jiang, Bin Wen, Fan Yang, Tingting Gao, Guorui Zhou, Liqiang Nie,
• Abstract summary: We propose controllable empathetic reasoning, which combines natural language reasoning with structured psychological steps.<n>We employ reinforcement learning with a unified process-outcome reward model that delivers precise feedback.<n>Our approach significantly improves model's emotional support ability, advancing the development of empathetic, human-like support systems.
• Score: 47.0476311232988
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Emotional support conversations are crucial for promoting emotional well-being, yet current models often lack deep empathetic reasoning grounded in psychological principles. To address this, we propose controllable empathetic reasoning, which combines natural language reasoning with structured psychological steps. We construct a fine-grained dataset annotated with reasoning correctness and response preferences to enable this capability. To further enhance training, we employ reinforcement learning with a unified process-outcome reward model that delivers precise feedback. To mitigate response repetitiveness from entropy collapse, we introduce personality-based dialogue rewriting and a redundancy-aware reward reweighting strategy. Our approach significantly improves model's emotional support ability, advancing the development of empathetic, human-like support systems.

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