EnvACE: Internalizing Environment Dynamics via World Rehearsal for Agentic Reinforcement Learning
DGX agentarXiv:2608.06197v1 Announce Type: new Abstract: Training large language model agents for long-horizon tool use typically relies on interactions with real or synthesized executable environments, whose