vLLM与NVIDIA等联合提出REINFORCE Zero算法
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2026年11月6日，vLLM官方博客发布报道，宣布vLLM联合NVIDIA Research等团队共同提出异步强化学习算法REINFORCE Zero。该成果主要针对异步强化学习中的算子失配难题，通过在采样引擎与训练器之间实现算子计算精度的完全对齐，达成了零失配的异步强化学习机制。目前相关技术方案已由vLLM及合作团队联合正式推出。
AI-generated from reports · Updated 11 hours ago
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- vLLM 官方博客SelectedvLLM Co-Introduces REINFORCE Zero: Zero-Mismatch Asynchronous Reinforcement Learning via Operator Alignment
In collaboration with NVIDIA Research and other teams, vLLM has introduced REINFORCE Zero. By fully aligning the operator computational precision between the sampling engine and the trainer, it resolves the operator mismatch challenge in asynchronous reinforcement learning.
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