Author

Zihao Yan

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Preprint Aug 2026

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

This paper proposes CRISP, a framework for training efficient deep search agents through critical step perception that distinguishes interactions that gather necessary evidence from redundant ones and shapes the training reward to preserve the former while pruning the latter, improving efficiency without sacrificing the evidence needed for correct answers.

Haosi Mo, Zihao Yan, Ruiqing Zhang et al. · 0 citations

Preprint Aug 2026

MAP-Graph: Provenance-Aware Shared Memory for Multi-Agent Workflows

MAP-Graph is introduced, a provenance-aware memory layer that represents agents, sources, memories, claims, and actions in a typed execution graph and supports provenance as an operational control signal, rather than only post-hoc audit metadata, within the evaluated setting.

Yiqi Wang, Zihao Yan, Jiaqi Zhang et al. · 3 citations