ThunderSyncRL speeds up synchronous agentic RL by up to 1.9x with zero policy staleness
StanfordAILab · x · 2026-10-10
ThunderSyncRL targets the inefficiency of synchronous GRPO-style agentic RL training, claiming up to 1.9x speedup with zero policy staleness.
Related event: ThunderSyncRL Speeds Up Synchronous Agentic RL by Up to 1.9x(2 posts)→
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