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<span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Digital Libraries">cs.DL</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> </div> </div> <p class="title is-5 mathjax"> pathfinder: A Semantic Framework for Literature Review and Knowledge Discovery in Astronomy </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Iyer%2C+K+G">Kartheik G. Iyer</a>, <a href="/search/cs?searchtype=author&query=Yunus%2C+M">Mikaeel Yunus</a>, <a href="/search/cs?searchtype=author&query=O%27Neill%2C+C">Charles O'Neill</a>, <a href="/search/cs?searchtype=author&query=Ye%2C+C">Christine Ye</a>, <a href="/search/cs?searchtype=author&query=Hyk%2C+A">Alina Hyk</a>, <a href="/search/cs?searchtype=author&query=McCormick%2C+K">Kiera McCormick</a>, <a href="/search/cs?searchtype=author&query=Ciuca%2C+I">Ioana Ciuca</a>, <a href="/search/cs?searchtype=author&query=Wu%2C+J+F">John F. Wu</a>, <a href="/search/cs?searchtype=author&query=Accomazzi%2C+A">Alberto Accomazzi</a>, <a href="/search/cs?searchtype=author&query=Astarita%2C+S">Simone Astarita</a>, <a href="/search/cs?searchtype=author&query=Chakrabarty%2C+R">Rishabh Chakrabarty</a>, <a href="/search/cs?searchtype=author&query=Cranney%2C+J">Jesse Cranney</a>, <a href="/search/cs?searchtype=author&query=Field%2C+A">Anjalie Field</a>, <a href="/search/cs?searchtype=author&query=Ghosal%2C+T">Tirthankar Ghosal</a>, <a href="/search/cs?searchtype=author&query=Ginolfi%2C+M">Michele Ginolfi</a>, <a href="/search/cs?searchtype=author&query=Huertas-Company%2C+M">Marc Huertas-Company</a>, <a href="/search/cs?searchtype=author&query=Jablonska%2C+M">Maja Jablonska</a>, <a href="/search/cs?searchtype=author&query=Kruk%2C+S">Sandor Kruk</a>, <a href="/search/cs?searchtype=author&query=Liu%2C+H">Huiling Liu</a>, <a href="/search/cs?searchtype=author&query=Marchidan%2C+G">Gabriel Marchidan</a>, <a href="/search/cs?searchtype=author&query=Mistry%2C+R">Rohit Mistry</a>, <a href="/search/cs?searchtype=author&query=Naiman%2C+J+P">J. P. Naiman</a>, <a href="/search/cs?searchtype=author&query=Peek%2C+J+E+G">J. E. G. Peek</a>, <a href="/search/cs?searchtype=author&query=Polimera%2C+M">Mugdha Polimera</a>, <a href="/search/cs?searchtype=author&query=Rodriguez%2C+S+J">Sergio J. Rodriguez</a> , et al. (5 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2408.01556v1-abstract-short" style="display: inline;"> The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with keywords.… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.01556v1-abstract-full').style.display = 'inline'; document.getElementById('2408.01556v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2408.01556v1-abstract-full" style="display: none;"> The exponential growth of astronomical literature poses significant challenges for researchers navigating and synthesizing general insights or even domain-specific knowledge. We present Pathfinder, a machine learning framework designed to enable literature review and knowledge discovery in astronomy, focusing on semantic searching with natural language instead of syntactic searches with keywords. Utilizing state-of-the-art large language models (LLMs) and a corpus of 350,000 peer-reviewed papers from the Astrophysics Data System (ADS), Pathfinder offers an innovative approach to scientific inquiry and literature exploration. Our framework couples advanced retrieval techniques with LLM-based synthesis to search astronomical literature by semantic context as a complement to currently existing methods that use keywords or citation graphs. It addresses complexities of jargon, named entities, and temporal aspects through time-based and citation-based weighting schemes. We demonstrate the tool's versatility through case studies, showcasing its application in various research scenarios. The system's performance is evaluated using custom benchmarks, including single-paper and multi-paper tasks. Beyond literature review, Pathfinder offers unique capabilities for reformatting answers in ways that are accessible to various audiences (e.g. in a different language or as simplified text), visualizing research landscapes, and tracking the impact of observatories and methodologies. This tool represents a significant advancement in applying AI to astronomical research, aiding researchers at all career stages in navigating modern astronomy literature. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2408.01556v1-abstract-full').style.display = 'none'; document.getElementById('2408.01556v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 2 August, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">25 pages, 9 figures, submitted to AAS jorunals. Comments are welcome, and the tools mentioned are available online at https://pfdr.app</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2405.20389">arXiv:2405.20389</a> <span> [<a href="https://arxiv.org/pdf/2405.20389">pdf</a>, <a href="https://arxiv.org/format/2405.20389">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Instrumentation and Methods for Astrophysics">astro-ph.IM</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Information Retrieval">cs.IR</span> </div> </div> <p class="title is-5 mathjax"> Designing an Evaluation Framework for Large Language Models in Astronomy Research </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/cs?searchtype=author&query=Wu%2C+J+F">John F. Wu</a>, <a href="/search/cs?searchtype=author&query=Hyk%2C+A">Alina Hyk</a>, <a href="/search/cs?searchtype=author&query=McCormick%2C+K">Kiera McCormick</a>, <a href="/search/cs?searchtype=author&query=Ye%2C+C">Christine Ye</a>, <a href="/search/cs?searchtype=author&query=Astarita%2C+S">Simone Astarita</a>, <a href="/search/cs?searchtype=author&query=Baral%2C+E">Elina Baral</a>, <a href="/search/cs?searchtype=author&query=Ciuca%2C+J">Jo Ciuca</a>, <a href="/search/cs?searchtype=author&query=Cranney%2C+J">Jesse Cranney</a>, <a href="/search/cs?searchtype=author&query=Field%2C+A">Anjalie Field</a>, <a href="/search/cs?searchtype=author&query=Iyer%2C+K">Kartheik Iyer</a>, <a href="/search/cs?searchtype=author&query=Koehn%2C+P">Philipp Koehn</a>, <a href="/search/cs?searchtype=author&query=Kotler%2C+J">Jenn Kotler</a>, <a href="/search/cs?searchtype=author&query=Kruk%2C+S">Sandor Kruk</a>, <a href="/search/cs?searchtype=author&query=Ntampaka%2C+M">Michelle Ntampaka</a>, <a href="/search/cs?searchtype=author&query=O%27Neill%2C+C">Charles O'Neill</a>, <a href="/search/cs?searchtype=author&query=Peek%2C+J+E+G">Joshua E. G. Peek</a>, <a href="/search/cs?searchtype=author&query=Sharma%2C+S">Sanjib Sharma</a>, <a href="/search/cs?searchtype=author&query=Yunus%2C+M">Mikaeel Yunus</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2405.20389v1-abstract-short" style="display: inline;"> Large Language Models (LLMs) are shifting how scientific research is done. It is imperative to understand how researchers interact with these models and how scientific sub-communities like astronomy might benefit from them. However, there is currently no standard for evaluating the use of LLMs in astronomy. Therefore, we present the experimental design for an evaluation study on how astronomy rese… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.20389v1-abstract-full').style.display = 'inline'; document.getElementById('2405.20389v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2405.20389v1-abstract-full" style="display: none;"> Large Language Models (LLMs) are shifting how scientific research is done. It is imperative to understand how researchers interact with these models and how scientific sub-communities like astronomy might benefit from them. However, there is currently no standard for evaluating the use of LLMs in astronomy. Therefore, we present the experimental design for an evaluation study on how astronomy researchers interact with LLMs. We deploy a Slack chatbot that can answer queries from users via Retrieval-Augmented Generation (RAG); these responses are grounded in astronomy papers from arXiv. We record and anonymize user questions and chatbot answers, user upvotes and downvotes to LLM responses, user feedback to the LLM, and retrieved documents and similarity scores with the query. Our data collection method will enable future dynamic evaluations of LLM tools for astronomy. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2405.20389v1-abstract-full').style.display = 'none'; document.getElementById('2405.20389v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 May, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">7 pages, 3 figures. 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