AI RESEARCH
Agentic Search in the Wild: Intents and Trajectory Dynamics from 14M+ Real Search Requests
arXiv CS.CL
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ArXi:2601.17617v3 Announce Type: replace-cross LLM-powered search agents are increasingly being used for multi-step information seeking tasks, yet the IR community lacks empirical understanding of how agentic search sessions unfold and how retrieved evidence is reflected in later queries. This paper presents a large-scale log analysis of agentic search based on 14.44M search requests (3.97M sessions) collected from DeepResearchGym, i.e., an open-source search API accessed by external agentic clients.