ThunderSyncRL: Lossless acceleration of agentic reinforcement learning
seilk.github.io · saved by 1 readers
ThunderSyncRL computes gradients while agent rollouts are still running, with one synchronous optimizer step per batch. Up to 1.9× faster to matched performance on SWE-bench Verified and Terminal Bench 4.0.