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Author

Yong Yu

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Preprint Aug 2026

What Makes Good Agentic Data? An ACE Lens on Data Generation for LLM Agents

This work represents agentic data as a common factorized object $(E,q,\tau,v)$, comprising an environment specification, task signal, interaction realization, and optional verifier, and formulate generation as constrained distribution design through the Accuracy-Complexity-divErsity (ACE) lens.

Xingshan Zeng, Zishan Xu, Bo-Ju Zhang et al. · 0 citations

From Final Artifacts to Trajectories: Retrospective Process Supervision for Evidence-Grounded Long-Form Generation

The key observation is that although expert trajectories are scarce, high-quality final artifacts such as literature reviews, analyst reports and legal judgments, are abundant in pre-training data and can be viewed as compressed traces of the evidence-seeking processes that produced them.

Junjie Huang, Jiarui Qin, Di Yin et al. · 0 citations

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