AI RESEARCH
ELITE: Experiential Learning and Intent-Aware Transfer for Self-improving Embodied Agents
arXiv CS.AI
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ArXi:2603.24018v1 Announce Type: new Vision-language models (VLMs) have shown remarkable general capabilities, yet embodied agents built on them fail at complex tasks, often skipping critical steps, proposing invalid actions, and repeating mistakes. These failures arise from a fundamental gap between the static