| A large annotated corpus for learning natural language inference SR Bowman, G Angeli, C Potts, CD Manning Proceedings of EMNLP, 2015 | 2124 | 2015 |
| 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 | 1741 | 2019 |
| Generating sentences from a continuous space SR Bowman, L Vilnis, O Vinyals, AM Dai, R Jozefowicz, S Bengio Proceedings of CoNLL, 2016 | 1564 | 2016 |
| A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference A Williams, N Nangia, SR Bowman Proceedings of NAACL-HLT, 2018 | 1311 | 2018 |
| Annotation artifacts in natural language inference data S Gururangan, S Swayamdipta, O Levy, R Schwartz, SR Bowman, ... Proceedings of NAACL, 2018 | 457 | 2018 |
| 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 | 437 | 2019 |
| XNLI: Evaluating Cross-lingual Sentence Representations A Conneau, G Lample, R Rinott, A Williams, SR Bowman, H Schwenk, ... Proceedings of EMNLP, 2018 | 396 | 2018 |
| Neural network acceptability judgments A Warstadt, A Singh, SR Bowman TACL 7, 625-641, 2019 | 320 | 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 | 311 | 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 | 307 | 2016 |
| Universal Dependencies 2.2 J Nivre, M Abrams, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, ... | 250* | 2018 |
| A Gold Standard Dependency Corpus for English N Silveira, T Dozat, MC de Marneffe, SR Bowman, M Connor, J Bauer, ... Proceedings of LREC, 2014 | 171 | 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 | 165* | 2015 |
| Sentence encoders on STILTs: Supplementary training on intermediate labeled-data tasks J Phang, T Févry, SR Bowman arXiv preprint 1811.01088, 2018 | 155 | 2018 |
| On Measuring Social Biases in Sentence Encoders C May, A Wang, S Bordia, SR Bowman, R Rudinger Proceedings of NAACL-HLT, 2019 | 128 | 2019 |
| 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 | 112* | 2018 |
| 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 | 70* | 2018 |
| Discourse-based objectives for fast unsupervised sentence representation learning Y Jernite, SR Bowman, D Sontag arXiv preprint arXiv:1705.00557, 2017 | 66 | 2017 |
| Speech recognition with segmental conditional random fields: A summary of the JHU CLSP 2010 summer workshop G Zweig, P Nguyen, D Van Compernolle, K Demuynck, L Atlas, P Clark, ... Proceedings of ICASSP, 5044-5047, 2011 | 66* | 2011 |
| Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling A Wang, J Hula, P Xia, R Pappagari, RT McCoy, R Patel, N Kim, I Tenney, ... Proceedings of ACL, 4465-4476, 2019 | 62* | 2019 |
Christopher D ManningProfessor of Computer Science and Linguistics, Stanford UniversityVerified email at stanford.edu
