Graham Neubig

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Satoshi NakamuraNara Institute of Science and TechnologyVerified email at is.naist.jp
Sakriani SaktiAssoc. Prof. of JAIST; Adjunct Assoc. Prof. of NAISTVerified email at is.naist.jp
Tomoki TodaNagoya UniversityVerified email at icts.nagoya-u.ac.jp
Antonis AnastasopoulosAssistant Professor, George Mason UniversityVerified email at gmu.edu
Pengcheng YinGoogleVerified email at google.com
Pengfei LiuCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Zhengbao JiangCarnegie Mellon UniversityVerified email at cs.cmu.edu
Paul MichelResearch Scientist, DeepMindVerified email at deepmind.com
Junjie HuAssistant Professor, University of Wisconsin-MadisonVerified email at wisc.edu
Junxian HeHong Kong University of Science and TechnologyVerified email at cse.ust.hk
Yusuke ODACTO, Inspired CognitionVerified email at legalforce.co.jp
Hiroaki HayashiSalesforce ResearchVerified email at salesforce.com
Taylor Berg-KirkpatrickUniversity of California San DiegoVerified email at ucsd.edu
Chunting ZhouFacebook AI ResearchVerified email at meta.com
Fangzheng (Frank) XuCarnegie Mellon UniversityVerified email at cs.cmu.edu
Xinyi WangResearch Scientist, GoogleVerified email at google.com
Shinnosuke TakamichiUniversity of TokyoVerified email at ipc.i.u-tokyo.ac.jp
Weizhe YuanNew York UniversityVerified email at nyu.edu
Kevin DuhJohns Hopkins UniversityVerified email at cs.jhu.edu
Matthias SperberAppleVerified email at apple.com

Graham Neubig

Carnegie Mellon University

Verified email at cs.cmu.edu - Homepage

Natural Language Processing Machine Learning


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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 ACM Computing Surveys, 2021	1765	2021
How can we know what language models know? Z Jiang, FF Xu, J Araki, G Neubig TACL 8, 423-438, 2020	761	2020
Are Sixteen Heads Really Better than One? P Michel, O Levy, G Neubig NeurIPS 2019, 2019	746	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	701	2020
A Syntactic Neural Model for General-Purpose Code Generation P Yin, G Neubig ACL 2017, 2017	662	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	433*	2017
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data P Yin, G Neubig, W Yih, S Riedel ACL 2020, 2020	361	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	346	2018
Pointwise prediction for robust, adaptable Japanese morphological analysis G Neubig, Y Nakata, S Mori ACL 2011, 529-533, 2011	340	2011
Towards a unified view of parameter-efficient transfer learning J He, C Zhou, X Ma, T Berg-Kirkpatrick, G Neubig ICLR 2022, 2022	316	2022
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	315	2015
BARTScore: Evaluating Generated Text as Text Generation W Yuan, G Neubig, P Liu NeurIPS 2021, 2021	306	2021
Stress Test Evaluation for Natural Language Inference A Naik, A Ravichander, N Sadeh, C Rose, G Neubig COLING 2018, 2018	306	2018
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders J He, D Spokoyny, G Neubig, T Berg-Kirkpatrick ICLR 2019, 2019	291	2019
Controllable Invariance through Adversarial Feature Learning Q Xie, Z Dai, Y Du, E Hovy, G Neubig NIPS 2017, 2017	266	2017
Competence-based Curriculum Learning for Neural Machine Translation EA Platanios, O Stretcu, G Neubig, B Poczos, TM Mitchell NAACL 2019, 2019	259	2019
Weight Poisoning Attacks on Pre-trained Models K Kurita, P Michel, G Neubig ACL 2020, 2020	243	2020
Controlling output length in neural encoder-decoders Y Kikuchi, G Neubig, R Sasano, H Takamura, M Okumura EMNLP 2016, 2016	239	2016
Neural machine translation and sequence-to-sequence models: A tutorial G Neubig arXiv preprint arXiv:1703.01619, 2017	227	2017
Incorporating discrete translation lexicons into neural machine translation P Arthur, G Neubig, S Nakamura EMNLP 2016, 2016	216	2016

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