Amortizing Sequential Experimental Design in Reasoning LLMs

What this work does

Trains an LLM’s action-selection reasoning with information-gain rewards so it can conduct sequential Bayesian experimental design more cheaply and generalize its information-gathering behavior to unseen categories and clinical dialogue.