arXiv:2605.27066v1 Announce Type: new Abstract: Understanding how events evolve over time is essential for search engines handling queries about trending news. We present QDET (Query-Driven Event Timeline Summarization), a production system deployed on Baidu Search that constructs focused event timelines to explain specific query events. Unlike traditional topic-centric approaches that aim for comprehensive coverage, QDET identifies and organizes sub-events closely relevant to the query from noisy candidate sets formed by millions of documents retrieved daily. QDET incorporates two key innovat
The proliferation of real-time information and the advancement of large language models make it timely to develop systems that summarize live event timelines for search users.
This development indicates a shift in how search engines provide information, moving towards more intelligent, query-driven summarization rather than mere document retrieval, enhancing user experience and information relevance.
Search engines will become more capable of synthesizing vast amounts of real-time data into coherent, event-specific timelines, significantly improving the utility of search for dynamic news and trending topics.
- · Baidu
- · Large Language Model developers
- · Users of search engines
- · Search engine providers
- · Traditional news aggregators (if they don't adapt)
- · Search engines without advanced summarization capabilities
Improved user satisfaction and engagement with search engines due to more relevant and organized event information.
Increased competition among search engine providers to implement sophisticated AI-driven summarization and timeline generation features.
Potential for new business models around highly personalized, real-time event intelligence feeds derived from similar technologies.
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Read at arXiv cs.CL