Andrew M. Bean

Oxford Internet Institute

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Andrew Bean is a doctoral researcher in Social Data Science at the Oxford Internet Institute. He studies data-centric machine learning from a technical and sociotechnical perspective.

Andrew has particular expertise in the study of large language models, and has co-authored research papers and policy briefs about benchmarking, alignment, bias and safety appearing in venues such as NeurIPS (2x Oral presentations), EMNLP, and the UK House of Lords. In 2022, he was awarded the Clarendon Scholarship for top doctoral applicants to the University of Oxford.

selected publications

  1. The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values
    Hannah Kirk, Andrew Bean, Bertie Vidgen, Paul Rottger, and Scott Hale
    In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Dec 2023
  2. The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models
    Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew M. Bean, Katerina Margatina, Juan Ciro, Rafael Mosquera, Max Bartolo, Adina Williams, He He, Bertie Vidgen, and Scott A. Hale
    Apr 2024
  3. LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages
    Andrew M. Bean, Simi Hellsten, Harry Mayne, Jabez Magomere, Ethan A. Chi, Ryan Chi, Scott A. Hale, and Hannah Rose Kirk
    Jun 2024