LLMScholarBench - Base Audits (datasets)

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Authors: Lisette Espín-Noboa
Cited by: 0

Abstract

This dataset contains the results of a systematic audit of six large language models in the context of scholar recommendation. The data include model-generated recommendations and derived evaluation outputs used in the analysis reported in "Whose Name Comes Up? Auditing LLM-Based Scholar Recommendations" (arXiv:2506.00074, version 2).

Fields of Study & Subjects

Ethics and Social Impacts of AI Recommender Systems and Techniques Topic Modeling

Publication details

Publication date
1 January 2026
Document type
Preprint