LLMs reshape scientific citation, citing less critically and more broadly

A new study published on arXiv reveals that large language models (LLMs) are reshaping scientific citation practices. Researchers found that LLMs tend to cite less critically than humans, favoring older and more popular papers. Additionally, LLMs over-cite authors who are socially distant from the citation context, unlike human writers who often cite within their closer networks. These findings suggest LLMs may broaden the reach of citations but also amplify visibility biases and reduce critical engagement with recent, niche work. AI

RANK_REASON The cluster contains a research paper published on arXiv detailing findings about LLM behavior. [lever_c_demoted from research: ic=1 ai=1.0]

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