BED-LLM: Intelligent Information Gathering with LLMs and Bayesian Experimental Design

ArXi:2508.21184v3 Announce Type: replace-cross We propose a general-purpose approach for improving the ability of large language models (LLMs) to intelligently and adaptively gather information from a user or other external source using the framework of sequential Bayesian experimental design (BED). This enables LLMs to act as effective multi-turn conversational agents and interactively interface with external environments.