Miguel Ballesteros

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	总计	2020 年至今
引用	12293	7483
h 指数	37	30
i10 指数	69	52

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Chris DyerDeepMind, Carnegie Mellon在 google.com 的电子邮件经过验证
Guillaume LampleMistral AI在 mistral.ai 的电子邮件经过验证
Noah A. SmithUniversity of Washington; Allen Institute for Artificial Intelligence在 cs.washington.edu 的电子邮件经过验证
Joakim NivreProfessor of Computational Linguistics, Uppsala University; Senior Researcher, RISE在 lingfil.uu.se 的电子邮件经过验证
Graham NeubigCarnegie Mellon University, All Hands AI在 cs.cmu.edu 的电子邮件经过验证
Adhiguna KuncoroOxford University and Google DeepMind在 google.com 的电子邮件经过验证
Jie MaApplied Scientist, Amazon在 amazon.com 的电子邮件经过验证
Leo WannerICREA Research Professor, Pompeu Fabra University在 upf.edu 的电子邮件经过验证
Austin MatthewsCarnegie Mellon University在 cmu.edu 的电子邮件经过验证
Shuai WangSenior Applied Scientist, Amazon在 amazon.com 的电子邮件经过验证
Pablo GervásCatedrático de Universidad在 ucm.es 的电子邮件经过验证
Yoav GoldbergProfessor, Bar Ilan University. Research Director, AI2-Israel在 cs.biu.ac.il 的电子邮件经过验证
Rishita AnubhaiPrincipal Applied Scientist, Amazon在 amazon.com 的电子邮件经过验证
Waleed AmmarGoogle在 google.com 的电子邮件经过验证
Virginia FranciscoTenured Professor of Computer Science, University Complutense of Madrid在 fdi.ucm.es 的电子邮件经过验证
Francesco BarbieriMeta在 meta.com 的电子邮件经过验证
Simon MilleADAPT Research Centre, Dublin City University在 adaptcentre.ie 的电子邮件经过验证
Horacio SaggionChair in Computer Science & Artificial Intelligence, Universitat Pompeu Fabra, DTIC. Head of TALN.在 upf.edu 的电子邮件经过验证
Bernd BohnetResearch Scientist, Google Deep Mind在 google.com 的电子邮件经过验证
Dan RothProfessor of Computer Science, University of Pennsylvania在 seas.upenn.edu 的电子邮件经过验证

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Miguel Ballesteros

Principal Applied Scientist, Amazon

在 amazon.com 的电子邮件经过验证 - 首页

Natural Language Processing Deep Learning Computational Linguistics


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Neural Architectures for Named Entity Recognition G Lample, M Ballesteros, S Subramanian, K Kawakami, C Dyer Proceedings of NAACL 2016, 2016	5596	2016
Transition-Based Dependency Parsing with Stack Long Short-Term Memory C Dyer, M Ballesteros, W Ling, A Matthews, NA Smith Proceedings of ACL 2015, 2015	1064	2015
Recurrent Neural Network Grammars C Dyer, A Kuncoro, M Ballesteros, N Smith Proceedings of NAACL 2016, 2016	774*	2016
Dynet: The dynamic neural network toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint arXiv:1701.03980, 2017	464*	2017
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs M Ballesteros, C Dyer, NA Smith Proceedings of EMNLP 2015, 2015	355	2015
Many languages, one parser W Ammar, G Mulcaire, M Ballesteros, C Dyer, NA Smith Transactions of the Association for Computational Linguistics (TACL), 2016	290	2016
Neural Language Models as Psycholinguistic Subjects: Representations of Syntactic State R Futrell, E Wilcox, T Morita, P Qian, M Ballesteros, R Levy Proceedings of NAACL 2019, 2019	238	2019
Detecting readers with dyslexia using machine learning with eye tracking measures L Rello, M Ballesteros Proceedings of the 12th international web for all conference, 1-8, 2015	232	2015
What Do Recurrent Neural Network Grammars Learn About Syntax? A Kuncoro, M Ballesteros, L Kong, C Dyer, G Neubig, NA Smith Proceedings EACL 2017, 2017	174	2017
Are Emojis Predictable? F Barbieri, M Ballesteros, H Saggion Proceedings of Short Papers EACL 2017, 2017	171	2017
Semeval 2018 task 2: Multilingual emoji prediction F Barbieri, J Camacho-Collados, F Ronzano, LE Anke, M Ballesteros, ... Proceedings of the 12th international workshop on semantic evaluation, 24-33, 2018	162	2018
Universal Dependencies 1.2 J Nivre, Ž Agić, MJ Aranzabe, M Asahara, A Atutxa, M Ballesteros, J Bauer, ... Universal Dependencies Consortium, 2015	160	2015
Universal dependencies 2.5 D Zeman, J Nivre, M Abrams, E Ackermann, N Aepli, H Aghaei, R Ziane LINDAT/CLARIAHCZ digital library at the Institute of Formal and Applied …, 2020	159*	2020
Universal dependencies 2.0 J Nivre, Ž Agić, L Ahrenberg, MJ Aranzabe, M Asahara, A Atutxa, ... Universal Dependencies Consortium, 2017	113*	2017
Universal Dependencies 2.1 J Nivre, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, M Asahara, ... Universal Dependencies Consortium, 2017	96*	2017
Label Semantics for Few Shot Named Entity Recognition J Ma, M Ballesteros, S Doss, R Anubhai, S Mallya, Y Al-Onaizan, D Roth Proceedings of ACL 2022 - Findings, 2022	95	2022
Multilingual Neural Machine Translation with Task-Specific Attention G Blackwood, M Ballesteros, T Ward Proceedings of COLING 2018, 2018	94	2018
Scheduled Multi-Task Learning: From Syntax to Translation E Kiperwasser, M Ballesteros Transactions of the Association for Computational Linguistics, 2018 …, 2018	90	2018
Training with Exploration Improves a Greedy Stack-LSTM Parser M Ballesteros, Y Goldberg, C Dyer, NA Smith Proceedings of Short Papers EMNLP 2016, 2016	89	2016
Distilling an Ensemble of Greedy Dependency Parsers into One MST Parser A Kuncoro, M Ballesteros, L Kong, C Dyer, NA Smith Proceedings of EMNLP 2016, 2016	88	2016

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