AI RESEARCH

A Communication-Theoretic Framework for LLM Agents: Cost-Aware Adaptive Reliability

arXiv CS.AI

ArXi:2605.09121v1 Announce Type: cross Agents built on large language models (LLMs) rely on a range of reliability techniques, including retry, majority voting, and self-consistency, that have been developed in parallel rather than within a common analytical framework. We observe that an LLM sampled at temperature $T$ is a discrete stochastic channel $p(y \mid x)$ in the sense of Shannon's coding theory, and use this identity as the entry point for such a framework grounded in communication theory.