Kevin Gimpel

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Karen LivescuTTI-ChicagoPatvirtintas el. paštas ttic.edu
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligencePatvirtintas el. paštas cs.washington.edu
Dan HendrycksDirector of the Center for AI SafetyPatvirtintas el. paštas berkeley.edu
John WietingGoogle ResearchPatvirtintas el. paštas ttic.edu
Mohit BansalParker Distinguished Professor, Computer Science, UNC Chapel HillPatvirtintas el. paštas cs.unc.edu
Mingda ChenFAIR, MetaPatvirtintas el. paštas fb.com
Sam WisemanApple AI/MLPatvirtintas el. paštas apple.com
Chris DyerDeepMind, Carnegie MellonPatvirtintas el. paštas google.com
Zhenzhong LanSchool of Engineering, Westlake UniversityPatvirtintas el. paštas westlake.edu.cn
Lifu TuSalesforce AI ResearchPatvirtintas el. paštas ttic.edu
Brendan O'ConnorUniversity of Massachusetts AmherstPatvirtintas el. paštas cs.umass.edu
Dipanjan DasSenior Director of Research, Google DeepmindPatvirtintas el. paštas google.com
ZEWEI CHUGooglePatvirtintas el. paštas google.com
Shubham ToshniwalSenior Research Scientist, NVIDIAPatvirtintas el. paštas nvidia.com
Freda ShiAssistant Professor of Computer Science, University of WaterlooPatvirtintas el. paštas uwaterloo.ca
Nathan SchneiderAssociate Professor, Linguistics and Computer Science • Georgetown UniversityPatvirtintas el. paštas georgetown.edu
David McAllesterProfessor, Toyota Technological Institute at ChicagoPatvirtintas el. paštas ttic.edu
Jacob EisensteinGoogle ResearchPatvirtintas el. paštas google.com
Jeffrey FlaniganAssistant Professor, University of California Santa CruzPatvirtintas el. paštas ucsc.edu
Michael HeilmanCivis AnalyticsPatvirtintas el. paštas cs.cmu.edu

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Kevin Gimpel

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Patvirtintas el. paštas ttic.edu - Pagrindinis puslapis

Natural Language Processing Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	7567	2019
Gaussian error linear units (GELUs) D Hendrycks, K Gimpel arXiv preprint arXiv:1606.08415, 2016	5927	2016
A baseline for detecting misclassified and out-of-distribution examples in neural networks D Hendrycks, K Gimpel ICLR, 2017	3550	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	1337	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	976	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	959	2013
Adversarial example generation with syntactically controlled paraphrase networks M Iyyer, J Wieting, K Gimpel, L Zettlemoyer NAACL, 2018	769	2018
Towards universal paraphrastic sentence embeddings J Wieting, M Bansal, K Gimpel, K Livescu ICLR, 2016	723	2016
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise D Hendrycks, M Mazeika, D Wilson, K Gimpel NeurIPS, 2018	632	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	489	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	385	2014
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	376	2018
From paraphrase database to compositional paraphrase model and back J Wieting, M Bansal, K Gimpel, K Livescu, D Roth TACL, 2015	321	2015
Early methods for detecting adversarial images D Hendrycks, K Gimpel arXiv preprint arXiv:1608.00530, 2016	318	2016
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	305	2010
Charagram: Embedding words and sentences via character n-grams J Wieting, M Bansal, K Gimpel, K Livescu EMNLP, 2016	250	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	200	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	199*	2010
Beyond BLEU: Training Neural Machine Translation with Semantic Similarity J Wieting, T Berg-Kirkpatrick, K Gimpel, G Neubig ACL 2019, 2019	166	2019
Who did what: A large-scale person-centered cloze dataset T Onishi, H Wang, M Bansal, K Gimpel, D McAllester EMNLP, 2016	164	2016

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