| Neural network acceptability judgments A Warstadt, A Singh, SR Bowman Transactions of the Association for Computational Linguistics 7, 625--641, 2019 | 1344 | 2019 |
| 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 | 1032 | 2022 |
| BLiMP: The benchmark of linguistic minimal pairs for English A Warstadt, A Parrish, H Liu, A Mohananey, W Peng, SF Wang, ... Transactions of the Association for Computational Linguistics 8, 377-392, 2020 | 397 | 2020 |
| Learning which features matter: RoBERTa acquires a preference for linguistic generalizations (eventually) A Warstadt, Y Zhang, HS Li, H Liu, SR Bowman EMNLP, 2020 | 134 | 2020 |
| When do you need billions of words of pretraining data? Y Zhang, A Warstadt, HS Li, SR Bowman ACL, 2020 | 133 | 2020 |
| Investigating BERT's knowledge of language: five analysis methods with NPIs A Warstadt, Y Cao, I Grosu, W Peng, H Blix, Y Nie, A Alsop, S Bordia, ... EMNLP, 2019 | 130 | 2019 |
| Are natural language inference models IMPPRESsive? Learning IMPlicature and PRESupposition P Jeretic, A Warstadt, S Bhooshan, A Williams ACL, 2020 | 110 | 2020 |
| Findings of the BabyLM Challenge: Sample-efficient pretraining on developmentally plausible corpora A Warstadt, A Mueller, L Choshen, E Wilcox, C Zhuang, J Ciro, ... Proceedings of the BabyLM Challenge at the 27th Conference on Computational …, 2023 | 100* | 2023 |
| What artificial neural networks can tell us about human language acquisition A Warstadt, SR Bowman Algebraic structures in natural language, 17-60, 2022 | 99 | 2022 |
| Can neural networks acquire a structural bias from raw linguistic data? A Warstadt, SR Bowman CogSci, 2020 | 72 | 2020 |
| Verb argument structure alternations in word and sentence embeddings K Kann, A Warstadt, A Williams, SR Bowman SCiL, 2018 | 49 | 2018 |
| Linguistic analysis of pretrained sentence encoders with acceptability judgments A Warstadt, SR Bowman arXiv preprint arXiv:1901.03438, 2019 | 41 | 2019 |
| Does putting a linguist in the loop improve NLU data collection? A Parrish, W Huang, O Agha, SH Lee, N Nangia, A Warstadt, K Aggarwal, ... ACL findings, 2021 | 40 | 2021 |
| CLiMP: A benchmark for Chinese language model evaluation B Xiang, C Yang, Y Li, A Warstadt, K Kann EACL, 2021 | 33 | 2021 |
| What ingredients make for an effective crowdsourcing protocol for difficult NLU data collection tasks? N Nangia, S Sugawara, H Trivedi, A Warstadt, C Vania, SR Bowman ACL, 2021 | 29 | 2021 |
| NOPE: A corpus of naturally-occurring presuppositions in English A Parrish, S Schuster, A Warstadt, O Agha, SH Lee, Z Zhao, SR Bowman, ... CoNLL, 2021 | 22 | 2021 |
| Entailment semantics can be extracted from an ideal language model W Merrill, A Warstadt, T Linzen Proceedings of the 26th Conference on Computational Natural Language …, 2022 | 14 | 2022 |
| What Makes Reading Comprehension Questions Difficult? S Sugawara, N Nangia, A Warstadt, SR Bowman arXiv preprint arXiv:2203.06342, 2022 | 13 | 2022 |
| "Just" don’t ask: Exclusives and potential questions A Warstadt Proceedings of Sinn und Bedeutung 24 (2), 373-390, 2020 | 7 | 2020 |
| A geometric notion of causal probing C Guerner, A Svete, T Liu, A Warstadt, R Cotterell arXiv preprint arXiv:2307.15054, 2023 | 6 | 2023 |
Samuel R. BowmanNYU and AnthropicVerified email at nyu.edu
