SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration

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Computer Science > Artificial Intelligence

arXiv:2607.15257v1 (cs)

[Submitted on 16 Jul 2026]

Title: SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration

Authors: Yuyao Zhang , Junjie Gao , Zhengxian Wu , Jiaming Fan , Jin Zhang , Shihan Ma , Yao Yao , Weiran Qi , Chuyan Jin , Guiyu Ma , Xingzhong Xu , Kai Yang , Ji-Rong Wen , Zhicheng Dou

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Abstract: Recent advances in Tool-Integrated Large Language Models have made web search a core capability of information-seeking agents. However, as interaction histories grow, agents increasingly struggle to track task progress. When search attempts fail to yield useful evidence, current single- and multi-agent systems can become trapped in repetitive loops, wasting search budgets and ultimately compromising the quality and completeness of the final output. We introduce SearchOS, a system-level multi-agent framework that turns fragile, implicit search progress into explicit, persistent, and shared state. First, we formulate open-domain information seeking as relational schema completion with grounded citations, where agents discover entities, populate attributes across linked tables, and anchor each value to source evidence. Then

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