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AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories
LLM-based agents are increasingly deployed in real-world applications through tool-use APIs, yet training them for specific environments remains fundamentally difficult: real-world applications provide no pre-defined tasks or verifiers, no faithful simulators, and limited budget for large-scale envi
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