MISE proves that hindsight self-evaluation rewards equal minimizing mutual information plus KL divergence to a proxy policy, and experiments show 7B LLMs reaching GPT-4o-level results on validation tasks.
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Utilizing and Calibrating Hindsight Process Rewards via Reinforcement with Mutual Information Self-Evaluation
MISE proves that hindsight self-evaluation rewards equal minimizing mutual information plus KL divergence to a proxy policy, and experiments show 7B LLMs reaching GPT-4o-level results on validation tasks.