| Part-of-speech tagging for Twitter: Annotation, features, and experiments K Gimpel, N Schneider, B O'Connor, D Das, D Mills, J Eisenstein, ... ACL, 2011 | 1173 | 2011 |
| Albert: A lite bert for self-supervised learning of language representations Z Lan, M Chen, S Goodman, K Gimpel, P Sharma, R Soricut arXiv preprint arXiv:1909.11942, 2019 | 1004 | 2019 |
| Improved part-of-speech tagging for online conversational text with word clusters O Owoputi, B O’Connor, C Dyer, K Gimpel, N Schneider, NA Smith Proceedings of the 2013 conference of the North American chapter of the …, 2013 | 815 | 2013 |
| A baseline for detecting misclassified and out-of-distribution examples in neural networks D Hendrycks, K Gimpel ICLR, 2017 | 643 | 2017 |
| Towards universal paraphrastic sentence embeddings J Wieting, M Bansal, K Gimpel, K Livescu ICLR, 2016 | 468 | 2016 |
| Gaussian error linear units (gelus) D Hendrycks, K Gimpel arXiv preprint arXiv:1606.08415, 2016 | 380* | 2016 |
| Multi-perspective sentence similarity modeling with convolutional neural networks H He, K Gimpel, J Lin Proceedings of the 2015 conference on empirical methods in natural language …, 2015 | 346 | 2015 |
| Tailoring continuous word representations for dependency parsing M Bansal, K Gimpel, K Livescu Proceedings of the 52nd Annual Meeting of the Association for Computational …, 2014 | 329 | 2014 |
| Movie reviews and revenues: An experiment in text regression M Joshi, D Das, K Gimpel, NA Smith Human Language Technologies: The 2010 Annual Conference of the North …, 2010 | 254 | 2010 |
| From paraphrase database to compositional paraphrase model and back J Wieting, M Bansal, K Gimpel, K Livescu, D Roth TACL, 2015 | 241 | 2015 |
| Adversarial example generation with syntactically controlled paraphrase networks M Iyyer, J Wieting, K Gimpel, L Zettlemoyer NAACL, 2018 | 227 | 2018 |
| Charagram: Embedding words and sentences via character n-grams J Wieting, M Bansal, K Gimpel, K Livescu EMNLP, 2016 | 169 | 2016 |
| Softmax-margin CRFs: Training log-linear models with cost functions K Gimpel, NA Smith Human Language Technologies: The 2010 Annual Conference of the North …, 2010 | 169* | 2010 |
| Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise D Hendrycks, M Mazeika, D Wilson, K Gimpel NeurIPS, 2018 | 152 | 2018 |
| Early methods for detecting adversarial images D Hendrycks, K Gimpel arXiv preprint arXiv:1608.00530, 2016 | 138 | 2016 |
| Deep multilingual correlation for improved word embeddings A Lu, W Wang, M Bansal, K Gimpel, K Livescu Proceedings of the 2015 Conference of the North American Chapter of the …, 2015 | 133 | 2015 |
| ParaNMT-50M: Pushing the limits of paraphrastic sentence embeddings with millions of machine translations J Wieting, K Gimpel Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 128 | 2018 |
| Who did what: A large-scale person-centered cloze dataset T Onishi, H Wang, M Bansal, K Gimpel, D McAllester EMNLP, 2016 | 108 | 2016 |
| Part-of-speech tagging for Twitter: Word clusters and other advances O Owoputi, B O’Connor, C Dyer, K Gimpel, N Schneider School of Computer Science, Carnegie Mellon University, Tech. Rep, 2012 | 97 | 2012 |
| Machine comprehension with syntax, frames, and semantics H Wang, M Bansal, K Gimpel, D McAllester 53rd Annual Meeting of the Association for Computational Linguistics, 2015 | 88 | 2015 |
Noah A. SmithUniversity of Washington; Allen Institute for Artificial Intelligence確認したメール アドレス: cs.washington.edu
