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        <title>Extracting Published Discussions of 13,616 Galaxies with Language Models</title>
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            <namePart type="given">Alberto</namePart>
            <namePart type="family">Accomazzi</namePart>
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    <abstract>Astronomers often have difficulty determining whether an object, such as a star or galaxy of interest, has been discussed in the literature. Existing tools enable object identification and linking in papers but do not record whether an object was genuinely discussed in a paper or just appears in a table or catalog. We address this by using language model agents to identify galaxies discussed in more than two sentences across a corpus of 156,006 arXiv astro-ph papers and extract those discussions. We extract 44,332 discussions of individual galaxies containing 85,314 quotes from 18,641 papers. With sky coordinates for 98.2% of discussions, we group them into 13,616 galaxies. We bring these results together into GalaxyWiki, where users can find literature discussing galaxies, read what was said about them, and follow links to the source papers. The code, dataset, and webpage are available at https://github.com/NolanKoblischke/galaxywiki-paper.</abstract>
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%0 Conference Proceedings
%T Extracting Published Discussions of 13,616 Galaxies with Language Models
%A Koblischke, Nolan
%A Bovy, Jo
%Y Accomazzi, Alberto
%Y Ghosal, Tirthankar
%Y Grezes, Felix
%Y Lockhart, Kelly
%Y Alkan, Atilla Kaan
%S Proceedings of the 4th Workshop on Artificial Intelligence for Scientific Publications
%D 2026
%8 November
%I Association for Computational Linguistics
%C Hengqin, Zhuhai, China
%@ 979-8-89176-456-9
%F koblischke-bovy-2026-extracting
%X Astronomers often have difficulty determining whether an object, such as a star or galaxy of interest, has been discussed in the literature. Existing tools enable object identification and linking in papers but do not record whether an object was genuinely discussed in a paper or just appears in a table or catalog. We address this by using language model agents to identify galaxies discussed in more than two sentences across a corpus of 156,006 arXiv astro-ph papers and extract those discussions. We extract 44,332 discussions of individual galaxies containing 85,314 quotes from 18,641 papers. With sky coordinates for 98.2% of discussions, we group them into 13,616 galaxies. We bring these results together into GalaxyWiki, where users can find literature discussing galaxies, read what was said about them, and follow links to the source papers. The code, dataset, and webpage are available at https://github.com/NolanKoblischke/galaxywiki-paper.
%U https://aclanthology.org/2026.wasp-1.19/
%P 174-179

Markdown (Informal)

[Extracting Published Discussions of 13,616 Galaxies with Language Models](https://aclanthology.org/2026.wasp-1.19/) (Koblischke & Bovy, WASP 2026)

• Extracting Published Discussions of 13,616 Galaxies with Language Models (Koblischke & Bovy, WASP 2026)

ACL

• Nolan Koblischke and Jo Bovy. 2026. Extracting Published Discussions of 13,616 Galaxies with Language Models. In Proceedings of the 4th Workshop on Artificial Intelligence for Scientific Publications, pages 174–179, Hengqin, Zhuhai, China. Association for Computational Linguistics.