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News/Towards Better Training Signal: Advantage Clipped Policy Optimization
arxiv
PublishedOctober 1, 2026 at 4:00 AM
—neutral

Towards Better Training Signal: Advantage Clipped Policy Optimization

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arXiv:2609.36816v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a cornerstone for improving the reasoning capabilities of large language models (LLMs), but the need for on-policy data substantially limits training efficiency. Reusing off-policy data through importance sampling

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