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News/Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling
arxiv
PublishedJune 15, 2026 at 4:00 AM

Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling

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arXiv:2602.14169v2 Announce Type: replace-cross Abstract: Effective exploration is a key challenge in reinforcement learning for large language models: discovering high-quality trajectories within a limited sampling budget from the vast natural language sequence space. Existing methods face notable

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