| Bias out-of-the-box: An empirical analysis of intersectional occupational biases in popular generative language models HR Kirk, Y Jun, F Volpin, H Iqbal, E Benussi, F Dreyer, A Shtedritski, ... Advances in neural information processing systems 34, 2611-2624, 2021 | 218 | 2021 |
| Auditing large language models: a three-layered approach J Mökander, J Schuett, HR Kirk, L Floridi AI and Ethics 4 (4), 1085-1115, 2024 | 209 | 2024 |
| The benefits, risks and bounds of personalizing the alignment of large language models to individuals HR Kirk, B Vidgen, P Röttger, SA Hale Nature Machine Intelligence, 1-10, 2024 | 174* | 2024 |
| Semeval-2023 task 10: Explainable detection of online sexism HR Kirk, W Yin, B Vidgen, P Röttger arXiv preprint arXiv:2303.04222, 2023 | 136 | 2023 |
| Dataperf: Benchmarks for data-centric ai development M Mazumder, C Banbury, X Yao, B Karlaš, W Gaviria Rojas, S Diamos, ... Advances in Neural Information Processing Systems 36, 5320-5347, 2023 | 135 | 2023 |
| Xstest: A test suite for identifying exaggerated safety behaviours in large language models P Röttger, HR Kirk, B Vidgen, G Attanasio, F Bianchi, D Hovy arXiv preprint arXiv:2308.01263, 2023 | 125 | 2023 |
| A prompt array keeps the bias away: Debiasing vision-language models with adversarial learning H Berg, SM Hall, Y Bhalgat, W Yang, HR Kirk, A Shtedritski, M Bain Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the …, 2022 | 107 | 2022 |
| Hatemoji: A test suite and adversarially-generated dataset for benchmarking and detecting emoji-based hate HR Kirk, B Vidgen, P Röttger, T Thrush, SA Hale Proceedings of the 2022 Conference of the North American Chapter of the …, 2021 | 63 | 2021 |
| The PRISM Alignment Project: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models HR Kirk, A Whitefield, P Röttger, A Bean, K Margatina, J Ciro, R Mosquera, ... arXiv preprint arXiv:2404.16019, 2024 | 49 | 2024 |
| Handling and Presenting Harmful Text in NLP HR Kirk, A Birhane, B Vidgen, L Derczynski EMNLP Findings, 2022 | 49* | 2022 |
| Political compass or spinning arrow? towards more meaningful evaluations for values and opinions in large language models P Röttger, V Hofmann, V Pyatkin, M Hinck, HR Kirk, H Schütze, D Hovy arXiv preprint arXiv:2402.16786, 2024 | 48 | 2024 |
| Looking for a Handsome Carpenter! Debiasing GPT-3 Job Advertisements C Borchers, DS Gala, B Gilburt, E Oravkin, W Bounsi, YM Asano, HR Kirk Proceedings of the 4th workshop on gender bias in natural language …, 2022 | 47 | 2022 |
| 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 arXiv preprint arXiv:2310.07629, 2023 | 36 | 2023 |
| Assessing language model deployment with risk cards L Derczynski, HR Kirk, V Balachandran, S Kumar, Y Tsvetkov, MR Leiser, ... arXiv preprint arXiv:2303.18190, 2023 | 35 | 2023 |
| Memes in the Wild: Assessing the Generalizability of the Hateful Memes Challenge Dataset HR Kirk, Y Jun, P Rauba, G Wachtel, R Li, X Bai, N Broestl, M Doff-Sotta, ... Proceedings of the 5th Workshop on Online Abuse and Harms (WOAH 2021), 2021 | 33 | 2021 |
| Introducing v0. 5 of the ai safety benchmark from mlcommons B Vidgen, A Agrawal, AM Ahmed, V Akinwande, N Al-Nuaimi, N Alfaraj, ... arXiv preprint arXiv:2404.12241, 2024 | 30 | 2024 |
| Simplesafetytests: a test suite for identifying critical safety risks in large language models B Vidgen, N Scherrer, HR Kirk, R Qian, A Kannappan, SA Hale, P Röttger arXiv preprint arXiv:2311.08370, 2023 | 27 | 2023 |
| Visogender: A dataset for benchmarking gender bias in image-text pronoun resolution SM Hall, F Gonçalves Abrantes, H Zhu, G Sodunke, A Shtedritski, HR Kirk Advances in Neural Information Processing Systems 36, 2024 | 24 | 2024 |
| Casteist but not racist? quantifying disparities in large language model bias between india and the west K Khandelwal, M Tonneau, AM Bean, HR Kirk, SA Hale arXiv preprint arXiv:2309.08573, 2023 | 22 | 2023 |
| Adversarial Nibbler: An Open Red-Teaming Method for Identifying Diverse Harms in Text-to-Image Generation J Quaye, A Parrish, O Inel, C Rastogi, HR Kirk, M Kahng, E Van Liemt, ... The 2024 ACM Conference on Fairness, Accountability, and Transparency, 388-406, 2024 | 21* | 2024 |
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