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WorkRover: Scaling Long-Horizon Cowork Agent Training Via Recursive Environment Evolution
Scaling interactive environments is important for training long-horizon agents through reinforcement learning. These environments often require further testing and refinement after initial generation, and correcting defects in a task may also require updating its work context and verifier. However,
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