AI for Scientific Search

原始链接: https://arxiv.org/abs/2507.01903

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This Hacker News thread discusses the application of AI for scientific research, sparked by a link to an arXiv.org survey paper on the topic. Commenters are actively seeking tools and workflows to streamline research, focusing on tasks like finding relevant papers, extracting metadata, summarizing content, and generating relationship graphs. Several users share tools they've built or found useful. These include Tatevlab (a "Spotify" for research papers), metawoRld and DataFindR (R packages for "living reviews"), Elicit.com, exa.ai combined with LLMs, SturdyStatistics.com (offering statistical overviews via hierarchical mixture models), Undermind.ai, and PaperAI (an open-source option). Zotero integration is also mentioned as a potential direction. A mathematician laments the lack of effective mathematical search and discusses the use of o3. There's also a note about the distinction between AI in general and LLM-based AI.

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.