Probing an Embodied LLM: When Higher Observation Fidelity Hurts Problem Solving.

arXiv:2605.20072v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly proposed as cognitive components for robotic systems, yet their opaque decision processes make it difficult to explain success or failure in closed-loop embodied