| Neural network acceptability judgments A Warstadt, A Singh, SR Bowman Transactions of the Association for Computational Linguistics 7, 625--641, 2019 | 719 | 2019 |
| 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 | 155 | 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, ... arXiv preprint arXiv:1909.02597, 2019 | 88 | 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 | 68 | 2022 |
| Are natural language inference models IMPPRESsive? Learning IMPlicature and PRESupposition P Jeretic, A Warstadt, S Bhooshan, A Williams arXiv preprint arXiv:2004.03066, 2020 | 62 | 2020 |
| When do you need billions of words of pretraining data? Y Zhang, A Warstadt, HS Li, SR Bowman arXiv preprint arXiv:2011.04946, 2020 | 55 | 2020 |
| Learning which features matter: RoBERTa acquires a preference for linguistic generalizations (eventually) A Warstadt, Y Zhang, HS Li, H Liu, SR Bowman arXiv preprint arXiv:2010.05358, 2020 | 49 | 2020 |
| Verb argument structure alternations in word and sentence embeddings K Kann, A Warstadt, A Williams, SR Bowman arXiv preprint arXiv:1811.10773, 2018 | 36 | 2018 |
| Can neural networks acquire a structural bias from raw linguistic data? A Warstadt, SR Bowman arXiv preprint arXiv:2007.06761, 2020 | 31 | 2020 |
| Linguistic analysis of pretrained sentence encoders with acceptability judgments A Warstadt, SR Bowman arXiv preprint arXiv:1901.03438, 2019 | 26* | 2019 |
| 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 arXiv preprint arXiv:2106.00794, 2021 | 14 | 2021 |
| CLiMP: A benchmark for Chinese language model evaluation B Xiang, C Yang, Y Li, A Warstadt, K Kann arXiv preprint arXiv:2101.11131, 2021 | 10 | 2021 |
| 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, ... arXiv preprint arXiv:2104.07179, 2021 | 8 | 2021 |
| "Just" don’t ask: Exclusives and potential questions A Warstadt Proceedings of Sinn und Bedeutung 24 (2), 373-390, 2020 | 5 | 2020 |
| What artificial neural networks can tell us about human language acquisition A Warstadt, SR Bowman Algebraic Structures in Natural Language, 17-60, 2022 | 4 | 2022 |
| What Makes Reading Comprehension Questions Difficult? S Sugawara, N Nangia, A Warstadt, SR Bowman arXiv preprint arXiv:2203.06342, 2022 | 4 | 2022 |
| NOPE: A corpus of naturally-occurring presuppositions in English A Parrish, S Schuster, A Warstadt, O Agha, SH Lee, Z Zhao, SR Bowman, ... arXiv preprint arXiv:2109.06987, 2021 | 4 | 2021 |
| Right-node wrapping: A combinatory account A Warstadt Proceedings for ESSLLI 2015 workshop ‘Empirical advances in Categorial …, 2015 | 4 | 2015 |
| Entailment Semantics Can Be Extracted from an Ideal Language Model W Merrill, A Warstadt, T Linzen arXiv preprint arXiv:2209.12407, 2022 | 2 | 2022 |
| Non-resolving responses to polar questions: A revision to the QUD theory of relevance O Agha, A Warstadt Proceedings of Sinn und Bedeutung 24 (1), 17-34, 2020 | 2 | 2020 |
Samuel R. BowmanAssociate Professor, NYUVerified email at nyu.edu
