SOURCE-LINKED INTELLIGENCE
Data Citation for Large Language Models: A Challenge
Large language models increasingly mediate access to information, and a growing body of work asks whether they cite the sources behind their outputs. That work treats citation as a verification device and applies it to textual documents. Scholarly citation serves two further functions, credit and provenance, and it applies to data as much as to text. This paper argues that data citation for large language models is an open challenge, distinct from document-level citation grounding and harder to solve. We ask how such models should cite data so that outputs stay verifiable, provenance stays tra
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-26T11:44:55.000Z
First collected: 2026-09-21T09:22:01.459Z. This is not the publication date.