AI RESEARCH
Answer Bubbles: Information Exposure in AI-Mediated Search
arXiv CS.CL
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ArXi:2603.16138v1 Announce Type: cross Generative search systems are increasingly replacing link-based retrieval with AI-generated summaries, yet little is known about how these systems differ in sources, language, and fidelity to cited material. We examine responses to 11,000 real search queries across four systems -- vanilla GPT, Search GPT, Google AI Overviews, and traditional Google Search -- at three levels: source diversity, linguistic characterization of the generated summary, and source-summary fidelity.