Green AI R Schwartz, J Dodge, NA Smith, O Etzioni CACM 63 (December 2020), 54-63, 2020 | 1469 | 2020 |
Annotation Artifacts in Natural Language Inference Data S Gururangan, S Swayamdipta, O Levy, R Schwartz, SR Bowman, ... NAACL-HLT 2018, 2018 | 1211 | 2018 |
Knowledge Enhanced Contextual Word Representations ME Peters, M Neumann, RL Logan IV, R Schwartz, V Joshi, S Singh, ... EMNLP 2019, 2019 | 803 | 2019 |
SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference R Zellers, Y Bisk, R Schwartz, Y Choi EMNLP 2018, 2018 | 796 | 2018 |
Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping J Dodge, G Ilharco, R Schwartz, A Farhadi, H Hajishirzi, N Smith arXiv:2002.06305, 2020 | 606 | 2020 |
Dataset Cartography: Mapping and Diagnosing Datasets with Training Dynamics S Swayamdipta, R Schwartz, N Lourie, Y Wang, H Hajishirzi, NA Smith, ... EMNLP 2020, 2020 | 344 | 2020 |
Random Feature Attention H Peng, N Pappas, D Yogatama, R Schwartz, NA Smith, L Kong ICLR 2021, 2021 | 321 | 2021 |
Show Your Work: Improved Reporting of Experimental Results J Dodge, S Gururangan, D Card, R Schwartz, NA Smith EMNLP 2019, 2019 | 283 | 2019 |
A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications D Kang, W Ammar, B Dalvi, M van Zuylen, S Kohlmeier, E Hovy, ... NAACL 2018, 2018 | 206 | 2018 |
Authorship Attribution of Micro-Messages R Schwartz, O Tsur, A Rappoport, M Koppel EMNLP 2013, 2013 | 190 | 2013 |
The Right Tool for the Job: Matching Model and Instance Complexities R Schwartz, G Stanovsky, S Swayamdipta, J Dodge, NA Smith ACL 2020, 2020 | 161 | 2020 |
Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction. R Schwartz, R Reichart, A Rappoport CoNLL 2015, 2015 | 142 | 2015 |
Measuring the Carbon Intensity of AI in Cloud Instances J Dodge, T Prewitt, RTD Combes, E Odmark, R Schwartz, E Strubell, ... FAccT 2022, 2022 | 141 | 2022 |
The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task R Schwartz, M Sap, I Konstas, L Zilles, Y Choi, NA Smith CoNLL 2017, 2017 | 121 | 2017 |
Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets NF Liu, R Schwartz, NA Smith NAACL 2019, 2019 | 113 | 2019 |
Data Contamination: From Memorization to Exploitation I Magar, R Schwartz ACL 2022, 2022 | 107 | 2022 |
How well do distributional models capture different types of semantic knowledge? D Rubinstein, E Levi, R Schwartz, A Rappoport ACL 2015, 2015 | 86 | 2015 |
A Formal Hierarchy of RNN Architectures W Merrill, G Weiss, Y Goldberg, R Schwartz, NA Smith, E Yahav ACL 2020, 2020 | 79 | 2020 |
Efficient Methods for Natural Language Processing: A Survey M Treviso, T Ji, JU Lee, B van Aken, Q Cao, MR Ciosici, M Hassid, ... TACL, 2023 | 77 | 2023 |
Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? W Merrill, Y Goldberg, R Schwartz, NA Smith TACL, 2021 | 66 | 2021 |