Characterizing Web Search by Conversational LLM Agents: From Search Decisions and Strategies to Results and Responses
Conversational LLM agents increasingly rely on Web search, yet the end-to-end lifecycle of agentic search remains poorly understood. We present the first study of Web search across four major conversational platforms (ChatGPT, Claude, Grok, and DeepSeek), combining real-world user interactions (invivo) with controlled experiments using the same platform's models by their APIs (invitro). We investigate the quality of agentic decisions to invoke Web search, their strategies to formulate queries, the potential domain preferences in the search results they receive, and the choices they make when transforming search results into grounded responses. We find that Web-search decisions vary substa...
| Authors | Mahsa Amani, Seungeon Lee, Abhisek Dash et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 September 2026 |
| Last updated at source | 16 September 2026 |
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