2026 Graham Neubig: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	90	608	591	325	315	561	33374

Overview

Graham Neubig is affiliated with Carnegie Mellon University in the United States. Their research primarily focuses on the field of Computer Science, with specific work in various subfields including Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Signal Processing, and Computer Networks and Communications.

Their main areas of study encompass several topics such as:

Topic Modeling
Natural Language Processing Techniques
Multimodal Machine Learning Applications
Software Engineering Research
Text Readability and Simplification
Speech Recognition and Synthesis
Speech and dialogue systems

Neubig has contributed to numerous publications, with a significant number appearing in well-known venues. Frequent publication venues include:

arXiv (Cornell University)
Transactions of the Association for Computational Linguistics
Zenodo (CERN European Organization for Nuclear Research)
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Some of their recent papers are:

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing, 2022, ACM Computing Surveys
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing, 2021, arXiv (Cornell University)
BARTScore: Evaluating Generated Text as Text Generation, 2021, arXiv (Cornell University)
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization, 2020, arXiv (Cornell University)
Towards a Unified View of Parameter-Efficient Transfer Learning, 2021, arXiv (Cornell University)

Frequent collaborators in their research include:

Frank F. Xu
Antonios Anastasopoulos
Pengfei Liu
Shruti Rijhwani
Uri Alon

Best Publications

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing.

Pengfei Liu;Weizhe Yuan;Jinlan Fu;Zhengbao Jiang

3288
Citations
A systematic evaluation of large language models of code

Unknown

990
Citations
How Can We Know What Language Models Know

Zhengbao Jiang;Frank F. Xu;Jun Araki;Graham Neubig

832
Citations
A Syntactic Neural Model for General-Purpose Code Generation

Pengcheng Yin;Graham Neubig

632
Citations
DyNet: The Dynamic Neural Network Toolkit

Graham Neubig;Chris Dyer;Yoav Goldberg;Austin Matthews

546
Citations
Are Sixteen Heads Really Better than One

Paul Michel;Omer Levy;Graham Neubig

488
Citations
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalisation

Junjie Hu;Sebastian Ruder;Aditya Siddhant;Graham Neubig

479
Citations
TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data

Pengcheng Yin;Graham Neubig;Wen-tau Yih;Sebastian Riedel

441
Citations
When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?

Ye Qi;Devendra Singh Sachan;Matthieu Felix;Sarguna Janani Padmanabhan

344
Citations
Stress Test Evaluation for Natural Language Inference

Aakanksha Naik;Abhilasha Ravichander;Norman M. Sadeh;Carolyn Penstein Rosé

335
Citations
PAL: Program-aided Language Models

Unknown

323
Citations
BARTScore: Evaluating Generated Text as Text Generation

Weizhe Yuan;Graham Neubig;Pengfei Liu

319
Citations
Pointwise Prediction for Robust, Adaptable Japanese Morphological Analysis

Graham Neubig;Yosuke Nakata;Shinsuke Mori

313
Citations
Competence-based Curriculum Learning for Neural Machine Translation

Emmanouil Antonios Platanios;Otilia Stretcu;Graham Neubig;Barnabás Póczos

302
Citations
XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization

Junjie Hu;Sebastian Ruder;Aditya Siddhant;Graham Neubig

301
Citations
Weight Poisoning Attacks on Pretrained Models

Keita Kurita;Paul Michel;Graham Neubig

299
Citations
Learning to Generate Pseudo-Code from Source Code Using Statistical Machine Translation (T)

Yusuke Oda;Hiroyuki Fudaba;Graham Neubig;Hideaki Hata

298
Citations
Towards a Unified View of Parameter-Efficient Transfer Learning

Junxian He;Chunting Zhou;Xuezhe Ma;Taylor Berg-Kirkpatrick

278
Citations
Controllable Invariance through Adversarial Feature Learning

Qizhe Xie;Zihang Dai;Yulun Du;Eduard H. Hovy

229
Citations
Learning to mine aligned code and natural language pairs from stack overflow

Pengcheng Yin;Bowen Deng;Edgar Chen;Bogdan Vasilescu

214
Citations
MasakhaNER: Named Entity Recognition for African Languages

David Ifeoluwa Adelani;Jade Z. Abbott;Graham Neubig;Daniel D'souza

191
Citations
GSum: A General Framework for Guided Neural Abstractive Summarization

Zi-Yi Dou;Pengfei Liu;Hiroaki Hayashi;Zhengbao Jiang

190
Citations
Word Alignment by Fine-tuning Embeddings on Parallel Corpora.

Zi-Yi Dou;Graham Neubig

116
Citations
How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering

Zhengbao Jiang;Jun Araki;Haibo Ding;Graham Neubig

113
Citations
How Can We Know When Language Models Know

Zhengbao Jiang;Jun Araki;Haibo Ding;Graham Neubig

7
Citations

Frequent Co-Authors

Satoshi Nakamura Nara Institute of Science and Technology

Sakriani Sakti Nara Institute of Science and Technology

Tomoki Toda Nagoya University

Taylor Berg-Kirkpatrick University of California, San Diego

Jaime G. Carbonell Carnegie Mellon University

Alex Waibel Carnegie Mellon University

Yiming Yang Carnegie Mellon University

Chris Dyer Google (United States)

Eduard Hovy Carnegie Mellon University

Eiichiro Sumita National Institute of Information and Communications Technology

External Links

Personal website of Graham Neubig Google Scholar page

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