AI RESEARCH
NEXUS: Continual Learning of Symbolic Constraints for Safe and Robust Embodied Planning
arXiv CS.AI
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ArXi:2605.09387v1 Announce Type: new While Large Language Models (LLMs) have catalyzed progress in embodied intelligence, a fundamental gap between their inherent probabilistic uncertainty and the strict determinism and verifiable safety required in the physical world. To mitigate this gap, this paper