Miguel Ballesteros

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Citations	10753	9038
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Chris DyerDeepMind, Carnegie MellonVerified email at google.com
Guillaume LampleResearch Scientist, Facebook AI ResearchVerified email at fb.com
Sandeep SubramanianNVIDIAVerified email at umontreal.ca
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Kawakami KazuyaUniversity of Oxford, Department of Computer ScienceVerified email at cs.ox.ac.uk
Adhiguna KuncoroOxford University and Google DeepMindVerified email at google.com
Joakim NivreProfessor of Computational Linguistics, Uppsala University; Senior Researcher, RISEVerified email at lingfil.uu.se
Graham NeubigCarnegie Mellon UniversityVerified email at cs.cmu.edu
Leo WannerICREA Research Professor, Pompeu Fabra UniversityVerified email at upf.edu
Austin MatthewsCarnegie Mellon UniversityVerified email at cmu.edu
Pablo GervásCatedrático de UniversidadVerified email at ucm.es
Yoav GoldbergProfessor, Bar Ilan University. Research Director, AI2-IsraelVerified email at cs.biu.ac.il
Waleed AmmarGoogleVerified email at google.com
Virginia FranciscoAssistant Professor of Computer Science, University Complutense of MadridVerified email at fdi.ucm.es
Francesco BarbieriSenior Research Scientist, Snap Inc.Verified email at snap.com
Simon MilleADAPT Research Centre, Dublin City UniversityVerified email at adaptcentre.ie
Rishita AnubhaiPrincipal Applied Scientist, AmazonVerified email at amazon.com
Jie MaApplied Scientist, AmazonVerified email at amazon.com
Bernd BohnetResearch Scientist, GoogleVerified email at google.com
Shuai WangSenior Applied Scientist, AmazonVerified email at amazon.com

Miguel Ballesteros

Principal Applied Scientist, Amazon

Verified email at amazon.com - Homepage

Natural Language Processing Deep Learning Computational Linguistics


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Neural Architectures for Named Entity Recognition G Lample, M Ballesteros, S Subramanian, K Kawakami, C Dyer Proceedings of NAACL 2016, 2016	4827	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	1030	2015
Recurrent Neural Network Grammars C Dyer, A Kuncoro, M Ballesteros, N Smith Proceedings of NAACL 2016, 2016	692*	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	444*	2017
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs M Ballesteros, C Dyer, NA Smith Proceedings of EMNLP 2015, 2015	340	2015
Many languages, one parser W Ammar, G Mulcaire, M Ballesteros, C Dyer, NA Smith Transactions of the Association for Computational Linguistics (TACL), 2016	274	2016
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	181	2015
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	172	2019
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	158	2017
Are Emojis Predictable? F Barbieri, M Ballesteros, H Saggion Proceedings of Short Papers EACL 2017, 2017	151	2017
Universal dependencies 2.2 J Nivre, M Abrams, Z Agic, L Ahrenberg, L Antonsen, ... Universal Dependencies Consortium, 2018	142	2018
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	132	2018
Universal dependencies 2.0 J Nivre, Ž Agić, L Ahrenberg, MJ Aranzabe, M Asahara, A Atutxa, ... Universal Dependencies Consortium, 2017	117*	2017
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	114	2020
Training with Exploration Improves a Greedy Stack-LSTM Parser M Ballesteros, Y Goldberg, C Dyer, NA Smith Proceedings of Short Papers EMNLP 2016, 2016	86	2016
MaltOptimizer: an optimization tool for MaltParser M Ballesteros, J Nivre Proceedings of the Demonstrations at EACL 2012, 2012	86	2012
Scheduled Multi-Task Learning: From Syntax to Translation E Kiperwasser, M Ballesteros Transactions of the Association for Computational Linguistics, 2018 …, 2018	85	2018
Universal Dependencies 2.1 J Nivre, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, M Asahara, ... Universal Dependencies Consortium, 2017	85*	2017
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	83	2016
Multilingual Neural Machine Translation with Task-Specific Attention G Blackwood, M Ballesteros, T Ward Proceedings of COLING 2018, 2018	77	2018

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