David Bao

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.