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Preprint Jul 2026

WAR: Workload-Aware Rollouts for Synchronous Agentic Reinforcement Learning

This work proposes WAR, a workload-aware rollout system that substantially accelerates synchronous agentic RL by jointly optimizing decoding and scheduling, and provides a practical path toward scalable long-context agent training.

Ryan Xu, Atlas Zhao, David Bao et al. · 0 citations