LaGEA: Language Guided Embodied Agents for Robotic Manipulation
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来源：arXiv cs.RO发布时间待核实
arXiv:2509.23155v3 Announce Type: replace Abstract: Robotic manipulation benefits from foundation models that describe goals, but today's agents still lack a principled way to learn from their own mistakes. We ask whether natural language can serve as feedback, an error-reasoning signal that helps embodied agents diagnose what went wrong and correct course.