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Know What You Don't Know: Agentic Data Synthesis by Evolving Generation Space for Closed-Loop Learning
The continued improvement of large language models increasingly depends on synthetic experience, yet effective data synthesis for interactive agents requires not only executable and verifiable trajectories, but also interactions that provide learning value for the current task agent. Existing methods increasingly incor …