Research talk: Summarizing information across multiple documents and modalities
- Subhojit Som | Microsoft
- Microsoft Research Summit 2021 | The Future of Search & Recommendation
Search engines have evolved over time, from initially providing the most relevant URLs to user queries to providing information in response to user queries that summarize content from multiple web documents. Instead of clicking and reading the top search results and finding the information themselves, users can now rely on search engines to «»read»» these documents via long document machine reading comprehension techniques and present the relevant summary from various documents to them. With recent breakthroughs in natural language generation and understanding of multi-modality content, search engines can now return very rich information presented in a comprehensive and easy-to-consume way. In this presentation, we will talk about some of the technologies behind this experience and how we see technology evolving in the future.
Learn more about the 2021 Microsoft Research Summit: https://Aka.ms/researchsummit (opens in new tab)
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Subhojit Som
Principal Applied Science Manager
Microsoft
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The Future of Search & Recommendation
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Keynote: Universal search and recommendation
- Paul Bennett
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Research talk: System frontiers for dense retrieval
- Jason Li,
- Knut Risvik
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Research talk: Domain-specific pretraining for vertical search
- Tristan Naumann
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Panel: The future of search and recommendation: Beyond web search
- Eric Horvitz,
- Nitin Agrawal,
- Soumen Chakrabati
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Panel: Causality in search and recommendation systems
- Emre Kiciman,
- Amit Sharma,
- Dean Eckles
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