AI RESEARCH
From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents
arXiv CS.CL
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ArXi:2604.19775v1 Announce Type: cross Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments. Despite their growing capability to perform multi-step reasoning and decision-making tasks, internal mechanisms guiding their sequential behavior remain opaque. This paper presents a framework for interpreting the temporal evolution of concepts in LLM agents through a step-wise conformal lens. We