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What is Enhancing LLM Reasoning with IB Regularization about?

This paper introduces an information-theoretic framework called IB-aware reasoning optimization (IBRO) to enhance the reasoning capabilities of large language models (LLMs) through reinforcement learning with verifiable rewards (RLVR). The framework encourages LLMs to produce reasoning trajectories that are informative and generalizable, while a novel IB regularization method integrates seamlessly into existing RL-based training without significant computational overhead. Empirical results demonstrate consi

Author

Mariana

Language

EN