| Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity Y Lu, M Bartolo, A Moore, S Riedel, P Stenetorp arXiv preprint arXiv:2104.08786, 2021 | 1062 | 2021 |
| Dynabench: Rethinking benchmarking in NLP D Kiela, M Bartolo, Y Nie, D Kaushik, A Geiger, Z Wu, B Vidgen, G Prasad, ... arXiv preprint arXiv:2104.14337, 2021 | 422 | 2021 |
| Winoground: Probing vision and language models for visio-linguistic compositionality T Thrush, R Jiang, M Bartolo, A Singh, A Williams, D Kiela, C Ross Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 391 | 2022 |
| Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension M Bartolo, A Roberts, J Welbl, S Riedel, P Stenetorp arXiv preprint arXiv:2002.00293, 2020 | 183 | 2020 |
| Interpretation of Natural Language Rules in Conversational Machine Reading M Saeidi, M Bartolo, P Lewis, S Singh, T Rocktäschel, M Sheldon, ... arXiv preprint arXiv:1809.01494, 2018 | 182 | 2018 |
| 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 | 133 | 2023 |
| Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation M Bartolo, T Thrush, R Jia, S Riedel, P Stenetorp, D Kiela arXiv preprint arXiv:2104.08678, 2021 | 97 | 2021 |
| Aya dataset: An open-access collection for multilingual instruction tuning S Singh, F Vargus, D Dsouza, BF Karlsson, A Mahendiran, WY Ko, ... arXiv preprint arXiv:2402.06619, 2024 | 64 | 2024 |
| Aya 23: Open weight releases to further multilingual progress V Aryabumi, J Dang, D Talupuru, S Dash, D Cairuz, H Lin, B Venkitesh, ... arXiv preprint arXiv:2405.15032, 2024 | 59 | 2024 |
| 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, A Bean, K Margatina, J Ciro, R Mosquera, ... arXiv preprint arXiv:2404.16019, 2024 | 49 | 2024 |
| Human feedback is not gold standard T Hosking, P Blunsom, M Bartolo arXiv preprint arXiv:2309.16349, 2023 | 45* | 2023 |
| Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants M Bartolo, T Thrush, S Riedel, P Stenetorp, R Jia, D Kiela arXiv preprint arXiv:2112.09062, 2021 | 36 | 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 |
| Adversarial nibbler: A data-centric challenge for improving the safety of text-to-image models A Parrish, HR Kirk, J Quaye, C Rastogi, M Bartolo, O Inel, J Ciro, ... arXiv preprint arXiv:2305.14384, 2023 | 21* | 2023 |
| Dynatask: A framework for creating dynamic AI benchmark tasks T Thrush, K Tirumala, A Gupta, M Bartolo, P Rodriguez, T Kane, ... arXiv preprint arXiv:2204.01906, 2022 | 17 | 2022 |
| Undersensitivity in Neural Reading Comprehension J Welbl, P Minervini, M Bartolo, P Stenetorp, S Riedel arXiv preprint arXiv:2003.04808, 2020 | 15 | 2020 |
| DMLR: Data-centric Machine Learning Research--Past, Present and Future L Oala, M Maskey, L Bat-Leah, A Parrish, NM Gürel, TS Kuo, Y Liu, R Dror, ... arXiv preprint arXiv:2311.13028, 2023 | 11 | 2023 |
| Contrasting human-and machine-generated word-level adversarial examples for text classification M Mozes, M Bartolo, P Stenetorp, B Kleinberg, LD Griffin arXiv preprint arXiv:2109.04385, 2021 | 11 | 2021 |
| Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models S Land, M Bartolo arXiv preprint arXiv:2405.05417, 2024 | 10 | 2024 |
| Improving Reward Models with Synthetic Critiques Z Ye, F Greenlee-Scott, M Bartolo, P Blunsom, JA Campos, M Gallé arXiv preprint arXiv:2405.20850, 2024 | 7 | 2024 |
Sebastian RiedelHonorary Professor @ University College London, Researcher @ DeepMindVerified email at cs.ucl.ac.uk
