The Silent Scholar Problem: A Probabilistic Framework for Breaking Epistemic Asymmetry in LLM Agents

This article likely presents a novel approach to address a specific challenge in the design and application of Large Language Model (LLM) agents. The title suggests a focus on epistemic asymmetry, meaning unequal access to knowledge or understanding between agents. The use of a "probabilistic framework" indicates a statistical or uncertainty-aware method for tackling this problem. The source, ArXiv, confirms this is a research paper.