Miguel Ballesteros

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Chris DyerDeepMind, Carnegie MellonVerified email at google.com
Sandeep SubramanianNVIDIAVerified email at umontreal.ca
Guillaume LampleResearch Scientist, Facebook AI ResearchVerified email at fb.com
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Adhiguna KuncoroOxford University and Google DeepMindVerified email at google.com
Joakim NivreSenior Researcher, RISE; Professor of Computational Linguistics, Uppsala UniversityVerified email at ri.se
Kawakami KazuyaUniversity of Oxford, Department of Computer ScienceVerified email at cs.ox.ac.uk
Graham NeubigAssociate Professor of Computer Science, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Austin MatthewsCarnegie Mellon UniversityVerified email at cmu.edu
Yoav GoldbergProfessor, Bar Ilan UniversityVerified email at cs.biu.ac.il
Pablo GervásCatedrático de UniversidadVerified email at ucm.es
Leo WannerICREA Research Professor, Pompeu Fabra UniversityVerified email at upf.edu
Waleed AmmarGoogleVerified email at google.com
Virginia FranciscoAssistant Professor of Computer Science, University Complutense of MadridVerified email at fdi.ucm.es
Francesco BarbieriSnap Inc.Verified email at snap.com
Lingpeng KongGoogle DeepMind, The University of Hong KongVerified email at cs.hku.hk
Simon MilleADAPT Research Centre, Dublin City UniversityVerified email at adaptcentre.ie
Bernd BohnetResearch Scientist, GoogleVerified email at google.com
Horacio SaggionChair in Computer Science & Artificial Intelligence, Department of Information & CommunicationVerified email at upf.edu
Luz RelloIE Business School, IE UniversityVerified email at ie.edu

Miguel Ballesteros

Principal Applied Scientist, Amazon

Verified email at amazon.com - Homepage

Natural Language Processing Deep Learning Computational Linguistics all_pubs_hand_verified_to_be_actually_mine


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Neural Architectures for Named Entity Recognition G Lample, M Ballesteros, S Subramanian, K Kawakami, C Dyer Proceedings of NAACL 2016, 2016	4085	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	958	2015
Recurrent Neural Network Grammars C Dyer, A Kuncoro, M Ballesteros, N Smith Proceedings of NAACL 2016, 2016	586*	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	417*	2017
Improved Transition-Based Parsing by Modeling Characters instead of Words with LSTMs M Ballesteros, C Dyer, NA Smith Proceedings of EMNLP 2015, 2015	325	2015
Many languages, one parser W Ammar, G Mulcaire, M Ballesteros, C Dyer, NA Smith Transactions of the Association for Computational Linguistics (TACL), 2016	248	2016
Universal Dependencies 1.2 J Nivre, Ž Agić, MJ Aranzabe, M Asahara, A Atutxa, M Ballesteros, J Bauer, ... Universal Dependencies Consortium, 2015	174	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	139	2017
Are Emojis Predictable? F Barbieri, M Ballesteros, H Saggion Proceedings of Short Papers EACL 2017, 2017	132	2017
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	125	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	125	2015
Universal dependencies 2.0 J Nivre, Ž Agić, L Ahrenberg, MJ Aranzabe, M Asahara, A Atutxa, ... Universal Dependencies Consortium, 2017	119*	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	107	2018
Universal Dependencies 2.6 D Zeman, J Nivre, M Abrams, E Ackermann, N Aepli, Ž Agic, L Ahrenberg, ... Universal Dependencies Consortium, 2020	97	2020
MaltOptimizer: an optimization tool for MaltParser M Ballesteros, J Nivre Proceedings of the Demonstrations at EACL 2012, 2012	85	2012
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
Scheduled Multi-Task Learning: From Syntax to Translation E Kiperwasser, M Ballesteros Transactions of the Association for Computational Linguistics, 2018 …, 2018	80	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	80	2016
Universal Dependencies 2.1 J Nivre, Ž Agić, L Ahrenberg, L Antonsen, MJ Aranzabe, M Asahara, ... Universal Dependencies Consortium, 2017	79*	2017
MaltOptimizer: A System for MaltParser Optimization. M Ballesteros, J Nivre Proceedings of LREC 2012, 2012	72	2012

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