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News/ARMOR: Stabilizing On-Policy LLM RL with Off-Policy Anchor Samples
arxiv
PublishedJuly 22, 2026 at 4:00 AM
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ARMOR: Stabilizing On-Policy LLM RL with Off-Policy Anchor Samples

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arXiv:2607.10481v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has significantly enhanced the reasoning capabilities of large language models (LLMs), yet the training process remains notoriously fragile. In this work, we investigate a critical source of this instability: over-

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