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News/Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals
arxiv
PublishedMay 22, 2026 at 4:00 AM

Clipping Bottleneck: Stabilizing RLVR via Stochastic Recovery of Near-Boundary Signals

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arXiv:2605.22703v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a central paradigm for scaling LLM reasoning, yet its optimization often suffers from training instability and suboptimal convergence. Through a systematic dissection of clipping-base

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