Kevin Gimpel

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Karen LivescuTTI-ChicagoVerified email at ttic.edu
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Dan HendrycksDirector of the Center for AI Safety (advisor for xAI and Scale)Verified email at berkeley.edu
John WietingGoogle ResearchVerified email at ttic.edu
Mohit BansalParker Distinguished Professor, Computer Science, UNC Chapel HillVerified email at cs.unc.edu
Mingda ChenFAIR, MetaVerified email at fb.com
Sam WisemanApple AI/MLVerified email at apple.com
Chris DyerDeepMind, Carnegie MellonVerified email at google.com
Zhenzhong LanSchool of Engineering, Westlake UniversityVerified email at westlake.edu.cn
Brendan T. O'ConnorUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Lifu TuSalesforce AI ResearchVerified email at ttic.edu
Dipanjan DasSenior Director of Research, Google DeepmindVerified email at google.com
ZEWEI CHUGoogleVerified email at google.com
Shubham ToshniwalSenior Research Scientist, NVIDIAVerified email at nvidia.com
Freda ShiAssistant Professor of Computer Science, University of WaterlooVerified email at uwaterloo.ca
Nathan SchneiderAssociate Professor, Linguistics and Computer Science • Georgetown UniversityVerified email at georgetown.edu
David McAllesterProfessor, Toyota Technological Institute at ChicagoVerified email at ttic.edu
Jacob EisensteinGoogle ResearchVerified email at google.com
Jeffrey FlaniganAssistant Professor, University of California Santa CruzVerified email at ucsc.edu
Michael HeilmanCivis AnalyticsVerified email at cs.cmu.edu

Kevin Gimpel

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Natural Language Processing Machine Learning


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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	8364	2019
Gaussian error linear units (GELUs) D Hendrycks, K Gimpel arXiv preprint arXiv:1606.08415, 2016	7132	2016
A baseline for detecting misclassified and out-of-distribution examples in neural networks D Hendrycks, K Gimpel ICLR, 2017	3955	2017
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	1351	2011
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	1286	2022
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 Human Language Technologies: Conference of the North American Chapter of the …, 2013	965	2013
Adversarial example generation with syntactically controlled paraphrase networks M Iyyer, J Wieting, K Gimpel, L Zettlemoyer NAACL, 2018	821	2018
Towards universal paraphrastic sentence embeddings J Wieting, M Bansal, K Gimpel, K Livescu ICLR, 2016	750	2016
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise D Hendrycks, M Mazeika, D Wilson, K Gimpel NeurIPS, 2018	672	2018
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	498	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	394	2018
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	388	2014
Early methods for detecting adversarial images D Hendrycks, K Gimpel arXiv preprint arXiv:1608.00530, 2016	328	2016
From paraphrase database to compositional paraphrase model and back J Wieting, M Bansal, K Gimpel, K Livescu, D Roth TACL, 2015	326	2015
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	309	2010
Charagram: Embedding words and sentences via character n-grams J Wieting, M Bansal, K Gimpel, K Livescu EMNLP, 2016	255	2016
Commonsense knowledge base completion X Li, A Taheri, L Tu, K Gimpel Proceedings of the 54th Annual Meeting of the Association for Computational …, 2016	211	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	202*	2010
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity J Wieting, T Berg-Kirkpatrick, K Gimpel, G Neubig ACL 2019, 2019	183	2019
Who did what: A large-scale person-centered cloze dataset T Onishi, H Wang, M Bansal, K Gimpel, D McAllester EMNLP, 2016	166	2016

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