| GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding A Wang, A Singh, J Michael, F Hill, O Levy, SR Bowman Proceedings of ICLR, 2019 | 2889 | 2019 |
| A large annotated corpus for learning natural language inference SR Bowman, G Angeli, C Potts, CD Manning Proceedings of EMNLP, 2015 | 2807 | 2015 |
| A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference A Williams, N Nangia, SR Bowman Proceedings of NAACL-HLT, 2018 | 2062 | 2018 |
| Generating sentences from a continuous space SR Bowman, L Vilnis, O Vinyals, AM Dai, R Jozefowicz, S Bengio Proceedings of CoNLL, 2016 | 1966 | 2016 |
| SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems A Wang, Y Pruksachatkun, N Nangia, A Singh, J Michael, F Hill, O Levy, ... Proceedings of NeurIPS, 2019 | 789 | 2019 |
| Annotation artifacts in natural language inference data S Gururangan, S Swayamdipta, O Levy, R Schwartz, SR Bowman, ... Proceedings of NAACL, 2018 | 669 | 2018 |
| XNLI: Evaluating Cross-lingual Sentence Representations A Conneau, G Lample, R Rinott, A Williams, SR Bowman, H Schwenk, ... Proceedings of EMNLP, 2018 | 618 | 2018 |
| Neural network acceptability judgments A Warstadt, A Singh, SR Bowman TACL 7, 625-641, 2019 | 518 | 2019 |
| What do you learn from context? Probing for sentence structure in contextualized word representations I Tenney, P Xia, B Chen, A Wang, A Poliak, RT McCoy, N Kim, ... Proceedings of ICLR, 2019 | 456 | 2019 |
| A Fast Unified Model for Parsing and Sentence Understanding SR Bowman, J Gauthier, A Rastogi, R Gupta, CD Manning, C Potts Proceedings of ACL, 2016 | 342 | 2016 |
| Universal Dependencies 2.2 J Nivre, M Abrams, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, ... | 267* | 2018 |
| Sentence encoders on STILTs: Supplementary training on intermediate labeled-data tasks J Phang, T Févry, SR Bowman arXiv preprint 1811.01088, 2018 | 243 | 2018 |
| On Measuring Social Biases in Sentence Encoders C May, A Wang, S Bordia, SR Bowman, R Rudinger Proceedings of NAACL-HLT, 2019 | 221 | 2019 |
| A Gold Standard Dependency Corpus for English N Silveira, T Dozat, MC de Marneffe, SR Bowman, M Connor, J Bauer, ... Proceedings of LREC, 2014 | 217 | 2014 |
| Recursive Neural Networks Can Learn Logical Semantics SR Bowman, C Potts, CD Manning Proceedings of the 3rd Workshop on Continuous Vector Space Models and their …, 2015 | 178* | 2015 |
| Do latent tree learning models identify meaningful structure in sentences? A Williams, A Drozdov, SR Bowman Transactions of the Association for Computational Linguistics 6, 253-267, 2018 | 123* | 2018 |
| Identifying and Reducing Gender Bias in Word-Level Language Models S Bordia, SR Bowman Proceedings of the NAACL-HLT Student Research Workshop, 2019 | 118 | 2019 |
| 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, ... Proceedings of ACL, 2020 | 112 | 2020 |
| BLiMP: A benchmark of linguistic minimal pairs for english A Warstadt, A Parrish, H Liu, A Mohananey, W Peng, SF Wang, ... TACL, 2020 | 106 | 2020 |
| Language Modeling Teaches You More than Translation Does: Lessons Learned Through Auxiliary Task Analysis K Zhang, S Bowman Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and …, 2018 | 105* | 2018 |
Nikita NangiaNew York UniversityVerified email at nyu.edu
