| The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models HR Kirk, A Whitefield, P Röttger, AM Bean, K Margatina, R Mosquera, ... The Thirty-eighth Conference on Neural Information Processing Systems …, 2024 | 244* | 2024 |
| The Past, Present and Better Future of Feedback Learning in Large Language Models for Subjective Human Preferences and Values HR Kirk, AM Bean, B Vidgen, P Röttger, SA Hale Empirical Methods in Natural Language Processing, 2409–2430, 2023 | 72 | 2023 |
| Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Models K Khandelwal, M Tonneau, AM Bean, HR Kirk, SA Hale GoodIT '24: Proceedings of the 2024 International Conference on Information …, 2024 | 65* | 2024 |
| LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low Resource and Extinct Languages AM Bean, S Hellsten, H Mayne, J Magomere, E Chi, R Chi, SA Hale, ... Advances in Neural Information Processing Systems 37, 26224-26237, 2024 | 32 | 2024 |
| Clinical knowledge in LLMs does not translate to human interactions AM Bean, R Payne, G Parsons, HR Kirk, J Ciro, R Mosquera, ... arXiv preprint arXiv:2504.18919, 2025 | 12 | 2025 |
| Do Large Language Models have Shared Weaknesses in Medical Question Answering? AM Bean, K Korgul, F Krones, R McCraith, A Mahdi AIM-FM Workshop @ NeurIPS'24, arXiv: 2310.07225, 2024 | 10* | 2024 |
| LLMs Don’t Know Their Own Decision Boundaries: The Unreliability of Self-Generated Counterfactual Explanations H Mayne, RO Kearns, Y Yang, AM Bean, ED Delaney, C Russell, A Mahdi Proceedings of the 2025 Conference on Empirical Methods in Natural Language …, 2025 | 4 | 2025 |
| Measuring what Matters: Construct Validity in Large Language Model Benchmarks AM Bean, RO Kearns, A Romanou, FS Hafner, H Mayne, J Batzner, ... arXiv preprint arXiv:2511.04703, 2025 | 3 | 2025 |
| Evaluating Fine-Tuning Efficiency of Human-Inspired Learning Strategies in Medical Question Answering Y Yang, AM Bean, R McCraith, A Mahdi NeurIPS 2024 Workshop on Fine-Tuning in Modern Machine Learning: Principles …, 2024 | 3* | 2024 |
| LINGOLY-TOO: Disentangling Reasoning from Knowledge with Templatised Orthographic Obfuscation J Khouja, K Korgul, S Hellsten, L Yang, V Neacsu, H Mayne, R Kearns, ... arXiv preprint arXiv:2503.02972, 2025 | 1 | 2025 |
| Scales++: Compute Efficient Evaluation Subset Selection with Cognitive Scales Embeddings AM Bean, N Seedat, S Chen, JR Schwarz arXiv preprint arXiv:2510.26384, 2025 | | 2025 |
| Evaluating the role of 'Constitutions' for learning from AI feedback S Redgate, AM Bean, A Mahdi arXiv preprint arXiv:2411.10168, 2024 | | 2024 |
Hannah Rose KirkUniversity of OxfordVerified email at oii.ox.ac.uk
