Ars Technica - All content 10月28日 04:36
AI搜索结果与传统搜索差异分析
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文章分析了AI搜索结果与传统搜索的差异,指出AI搜索更倾向于引用不流行的网站和不在传统搜索前100条链接中的网站。

Since last year’s disastrous rollout of Google’s AI Overviews, the world at large has been aware of how AI-powered search results can differ wildly from the traditional list of links search engines have generated for decades. Now, new research helps quantify that difference, showing that AI search engines tend to cite less popular websites and ones that wouldn’t even appear in the Top 100 links listed in an “organic” Google search.

In the pre-print paper “Characterizing Web Search in The Age of Generative AI,” researchers from Ruhr University in Bochum and the Max Planck Institute for Software Systems compared traditional link results from Google’s search engine to its AI Overviews and Gemini-2.5-Flash. The researchers also looked at GPT-4o’s web search mode and the separate “GPT-4o with Search Tool,” which resorts to searching the web only when the LLM decides it needs information found outside its own pre-trained data.

The researchers drew test queries from a number of sources, including specific questions submitted to ChatGPT in the WildChat dataset, general political topics listed on AllSides, and products included in the 100 most-searched Amazon products list.

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AI搜索 传统搜索 搜索引擎 搜索结果
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