Graham Neubig

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Citations	14188	12652
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Satoshi NakamuraNara Institute of Science and TechnologyVerified email at is.naist.jp
Sakriani SaktiProject Associate Professor of Nara Institutes of Science and TechnologyVerified email at is.naist.jp
Tomoki TodaNagoya UniversityVerified email at icts.nagoya-u.ac.jp
Pengcheng YinGoogleVerified email at google.com
Antonis AnastasopoulosAssistant Professor, George Mason UniversityVerified email at gmu.edu
Paul MichelPost-doc, Center for Data Science/LSCP, École Normale SupérieureVerified email at inria.fr
Yusuke ODAHead of Machine Intelligence Unit, LegalForceVerified email at legalforce.co.jp
Junjie HuAssistant Professor, University of Wisconsin-MadisonVerified email at wisc.edu
Taylor Berg-KirkpatrickUniversity of California San DiegoVerified email at ucsd.edu
Chunting ZhouCarnegie Mellon UniversityVerified email at cs.cmu.edu
Xinyi WangPhD student, Carnegie Mellon UniversityVerified email at cs.cmu.edu
Junxian HeCarnegie Mellon UniversityVerified email at cs.cmu.edu
Kevin DuhJohns Hopkins UniversityVerified email at cs.jhu.edu
Shinnosuke TakamichiUniversity of TokyoVerified email at ipc.i.u-tokyo.ac.jp
Chris DyerDeepMind, Carnegie MellonVerified email at google.com
Matthias SperberAppleVerified email at apple.com
Tatsuya KawaharaProfessor, School of Informatics, Kyoto UniversityVerified email at i.kyoto-u.ac.jp
Zhengbao JiangCarnegie Mellon UniversityVerified email at cs.cmu.edu
Pengfei LiuCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Xuezhe MaInformation Sciences Institute, University of Southern CaliforniaVerified email at usc.edu

Graham Neubig

Associate Professor of Computer Science, Carnegie Mellon University

Verified email at cs.cmu.edu - Homepage

Natural Language Processing Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
A Syntactic Neural Model for General-Purpose Code Generation P Yin, G Neubig ACL 2017, 2017	478	2017
Dynet: The dynamic neural network toolkit G Neubig, C Dyer, Y Goldberg, A Matthews, W Ammar, A Anastasopoulos, ... arXiv preprint arXiv:1701.03980, 2017	401*	2017
Are Sixteen Heads Really Better than One? P Michel, O Levy, G Neubig NeurIPS 2019, 2019	399	2019
XTREME: A massively multilingual multi-task benchmark for evaluating cross-lingual generalization J Hu, S Ruder, A Siddhant, G Neubig, O Firat, M Johnson ICML 2020, 2020	364	2020
Pointwise prediction for robust, adaptable Japanese morphological analysis G Neubig, Y Nakata, S Mori ACL 2011, 529-533, 2011	306	2011
How can we know what language models know? Z Jiang, FF Xu, J Araki, G Neubig TACL 8, 423-438, 2020	262	2020
When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation? Y Qi, DS Sachan, M Felix, SJ Padmanabhan, G Neubig NAACL 2018, 2018	250	2018
Learning to generate pseudo-code from source code using statistical machine translation (t) Y Oda, H Fudaba, G Neubig, H Hata, S Sakti, T Toda, S Nakamura ASE 2015, 574-584, 2015	240	2015
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders J He, D Spokoyny, G Neubig, T Berg-Kirkpatrick ICLR 2019, 2019	212	2019
Controllable Invariance through Adversarial Feature Learning Q Xie, Z Dai, Y Du, E Hovy, G Neubig NIPS 2017, 2017	203	2017
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing P Liu, W Yuan, J Fu, Z Jiang, H Hayashi, G Neubig arXiv preprint arXiv:2107.13586, 2021	201	2021
Stress Test Evaluation for Natural Language Inference A Naik, A Ravichander, N Sadeh, C Rose, G Neubig COLING 2018, 2018	193	2018
Incorporating discrete translation lexicons into neural machine translation P Arthur, G Neubig, S Nakamura EMNLP 2016, 2016	185	2016
Controlling output length in neural encoder-decoders Y Kikuchi, G Neubig, R Sasano, H Takamura, M Okumura EMNLP 2016, 2016	177	2016
Neural machine translation and sequence-to-sequence models: A tutorial G Neubig arXiv preprint arXiv:1703.01619, 2017	172	2017
Stack-Pointer Networks for Dependency Parsing X Ma, Z Hu, J Liu, N Peng, G Neubig, E Hovy ACL 2018, 2018	154	2018
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data P Yin, G Neubig, W Yih, S Riedel ACL 2020, 2020	150	2020
Learning to translate in real-time with neural machine translation J Gu, G Neubig, K Cho, VOK Li EACL 2017, 2016	144	2016
What Do Recurrent Neural Network Grammars Learn About Syntax? A Kuncoro, M Ballesteros, L Kong, C Dyer, G Neubig, NA Smith EACL 2017, 2017	142	2017
Morphological inflection generation using character sequence to sequence learning M Faruqui, Y Tsvetkov, G Neubig, C Dyer NAACL 2016, 2016	139	2016

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