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EmpathyAgent: Can Embodied Agents Conduct Empathetic Actions?

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arxiv 2503.16545 v1 pith:BHU2FVP7 submitted 2025-03-19 cs.CY cs.CL

classification cs.CYcs.CL
keywords empatheticagentsactionsempathyagentbenchmarkembodiedremainsconduct
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Empathy is fundamental to human interactions, yet it remains unclear whether embodied agents can provide human-like empathetic support. Existing works have studied agents' tasks solving and social interactions abilities, but whether agents can understand empathetic needs and conduct empathetic behaviors remains overlooked. To address this, we introduce EmpathyAgent, the first benchmark to evaluate and enhance agents' empathetic actions across diverse scenarios. EmpathyAgent contains 10,000 multimodal samples with corresponding empathetic task plans and three different challenges. To systematically evaluate the agents' empathetic actions, we propose an empathy-specific evaluation suite that evaluates the agents' empathy process. We benchmark current models and found that exhibiting empathetic actions remains a significant challenge. Meanwhile, we train Llama3-8B using EmpathyAgent and find it can potentially enhance empathetic behavior. By establishing a standard benchmark for evaluating empathetic actions, we hope to advance research in empathetic embodied agents. Our code and data are publicly available at https://github.com/xinyan-cxy/EmpathyAgent.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Towards High-Level Semantic Intelligence

    cs.AI 2026-07 conditional novelty 4.0 of 10

    A survey proposing that AI's next stage should be understood as High-Level Semantic Intelligence: mastering humor, sarcasm, metaphor, empathy, persuasion, and narrative across modalities.

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