AI RESEARCH
Learning from Trials and Errors: Reflective Test-Time Planning for Embodied LLMs
arXiv CS.AI
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ArXi:2602.21198v2 Announce Type: replace-cross Embodied LLMs endow robots with high-level task reasoning, but they cannot reflect on what went wrong or why, turning deployment into a sequence of independent trials where mistakes repeat rather than accumulate into experience. Drawing upon human reflective practitioners, we