Enhancing Language Model Reasoning with Expert Iteration: Bridging the Gap Through Reinforcement Learning

The capabilities of LLMs are advancing rapidly, evidenced by their performance across various benchmarks in mathematics, science, and coding tasks. Concurrently, advancements in Reinforcement Learning from Human Feedback (RLHF) and instruction fine-tuning are aligning LLMs more closely with human preferences. This progress enhances the apparent abilities of LLMs, making complex behaviors more accessible through instruction […]

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