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Paper Information

lrec2026-ws-legal-04

Authorship Attribution in the Times of LLMs within the Framework of the CRediT Taxonomy

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Title

Authorship Attribution in the Times of LLMs within the Framework of the CRediT Taxonomy

Abstract

This article examines the concept of authorship in the context of generative language models and other uses of Artificial Intelligence, and how this new ‘authorshipness’ can be represented in metadata. It analyses authorship under copyright law and proposes a metadata-based approach to disclosing the use of AI in publications, drawing on the widely adopted CRediT taxonomy developed by the National Information Standards Organization (NISO), and informed by guidance from the United States Copyright Office (USCO) and the International Association of Scientific, Technical and Medical Publishers (STM).


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