Calibrating LLM Explanations to Human Decisions with Reinforcement Learning

Name: Calibrating LLM Explanations to Human Decisions with Reinforcement Learning
Uploaded: 2026-10-18T12:24:54.937879+00:00
Duration: 298 s
Description: HD-RL is a reinforcement learning framework that optimizes Large Language Model (LLM) explanations by training them against observed human decisions. It calibrates a decision simulator based on human behavior to generate explanations that improve the quality of human decision-making, leading to significantly higher detection accuracy compared to other methods.

HD-RL is a reinforcement learning framework that optimizes Large Language Model (LLM) explanations by training them against observed human decisions. It calibrates a decision simulator based on human behavior to generate explanations that improve the quality of human decision-making, leading to significantly higher detection accuracy compared to other methods.

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