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| Beyond the imitation game: Quantifying and extrapolating the capabilities of language models A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ... arXiv preprint arXiv:2206.04615, 2022 | 999 | 2022 |
| Gpt-neox-20b: An open-source autoregressive language model S Black, S Biderman, E Hallahan, Q Anthony, L Gao, L Golding, H He, ... arXiv preprint arXiv:2204.06745, 2022 | 693 | 2022 |
| Deep neural networks improve radiologists’ performance in breast cancer screening N Wu, J Phang, J Park, Y Shen, Z Huang, M Zorin, S Jastrzębski, T Févry, ... IEEE transactions on medical imaging 39 (4), 1184-1194, 2019 | 647 | 2019 |
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| Sentence encoders on stilts: Supplementary training on intermediate labeled-data tasks J Phang, T Févry, SR Bowman arXiv preprint arXiv:1811.01088, 2018 | 475 | 2018 |
| Intermediate-task transfer learning with pretrained models for natural language understanding: When and why does it work? Y Pruksachatkun, J Phang, H Liu, PM Htut, X Zhang, RY Pang, C Vania, ... arXiv preprint arXiv:2005.00628, 2020 | 294 | 2020 |
| BBQ: A hand-built bias benchmark for question answering A Parrish, A Chen, N Nangia, V Padmakumar, J Phang, J Thompson, ... arXiv preprint arXiv:2110.08193, 2021 | 235 | 2021 |
| An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization Y Shen, N Wu, J Phang, J Park, K Liu, S Tyagi, L Heacock, SG Kim, L Moy, ... Medical image analysis 68, 101908, 2021 | 171 | 2021 |
| Pretraining language models with human preferences T Korbak, K Shi, A Chen, RV Bhalerao, C Buckley, J Phang, SR Bowman, ... International Conference on Machine Learning, 17506-17533, 2023 | 152 | 2023 |
| Do attention heads in BERT track syntactic dependencies? PM Htut, J Phang, S Bordia, SR Bowman arXiv preprint arXiv:1911.12246, 2019 | 140 | 2019 |
| Investigating BERT’s Knowledge of Language: Five Analysis Methods with NPIs A Warstadt arXiv preprint arXiv:1909.02597, 2019 | 130 | 2019 |
| A framework for few-shot language model evaluation L Gao, J Tow, S Biderman, S Black, A DiPofi, C Foster, L Golding, J Hsu, ... Version v0. 0.1. Sept 10, 8-9, 2021 | 123 | 2021 |
| What language model to train if you have one million gpu hours? TL Scao, T Wang, D Hesslow, L Saulnier, S Bekman, MS Bari, ... arXiv preprint arXiv:2210.15424, 2022 | 93 | 2022 |
| QuALITY: Question answering with long input texts, yes! RY Pang, A Parrish, N Joshi, N Nangia, J Phang, A Chen, V Padmakumar, ... arXiv preprint arXiv:2112.08608, 2021 | 93 | 2021 |
| Unsupervised sentence compression using denoising auto-encoders T Fevry, J Phang arXiv preprint arXiv:1809.02669, 2018 | 79 | 2018 |
| English intermediate-task training improves zero-shot cross-lingual transfer too J Phang, I Calixto, PM Htut, Y Pruksachatkun, H Liu, C Vania, K Kann, ... arXiv preprint arXiv:2005.13013, 2020 | 69 | 2020 |
| A framework for few-shot language model evaluation, 12 2023 L Gao, J Tow, B Abbasi, S Biderman, S Black, A DiPofi, C Foster, ... URL https://zenodo. org/records/10256836 7, 0 | 59 | |
| Investigating efficiently extending transformers for long input summarization J Phang, Y Zhao, PJ Liu arXiv preprint arXiv:2208.04347, 2022 | 53 | 2022 |
| jiant 1.2: A software toolkit for research on general-purpose text understanding models A Wang, IF Tenney, Y Pruksachatkun, K Yu, J Hula, P Xia, R Pappagari, ... Note: http://jiant. info/Cited by: footnote 4, 2019 | 53 | 2019 |
Samuel R. BowmanNYU and AnthropicVerified email at nyu.edu
