Graham Neubig
Associate Professor, Language Technology Institute, Carnegie Mellon University
Affiliated Faculty, Machine Learning Department, Carnegie Mellon University
President, Inspired Cognition
My research is concerned with language and its role in human communication. In particular, my long-term research goal is to break down barriers in human-human or human-machine communication through the development of natural language processing (NLP) technologies. This includes the development of technology for machine translation, which helps break down barriers in communication for people who speak different languages, and natural language understanding, which helps computers understand and respond to human language. Within this overall goal of breaking down barriers to human communication, I have focused on several aspects of language that both make it interesting as a scientific subject, and hold potential for the construction of practical systems. Specific areas of interest include:
- Multilingual Language Processing
- Machine Translation
- Syntactic and Semantic Analysis
- Cross-lingual Learning
- Natural Language Interfaces to Computers
- Natural Language to Code Generation
- Question Answering and Information Extraction
- Modeling Human-Computer or Human-Human Interaction
- Machine Learning for NLP
- Explainability and Interpretable Evaluation
- Neural Network Models for NLP
- Unsupervised and Semi-supervised Learning
Academic/Career History
- 7/2020-onward Carnegie Mellon University (CMU): Associate Professor
- 9/2016-7/2020 Carnegie Mellon University (CMU): Assistant Professor
- 4/2012-8/2016 Nara Institute of Science and Technology (NAIST): Assistant Professor
- 4/2010-3/2012 Kyoto University: Doctoral course in Intelligent Information Systems
- 4/2008-3/2010 Kyoto University: Master's course in Intelligent Information Systems
- 8/2006-3/2008 Hyogo Prefectural Government: Coordinator for International Relations
- 9/2005-7/2006 Tajima Agricultural High School: Assistant Language Teacher
- 8/2001-5/2005 University of Illinois, Urbana-Champaign: B.S. Computer Science
Papers
Here is a list of a few of my current favorite papers:
- Vijay Viswanathan, Luyu Gao, Tongshuang Wu, Pengfei Liu, Graham Neubig.
DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions (BibTex, Code/Data)
Annual Conference of the Association for Computational Linguistics (ACL). Toronto, Canada. July 2023 (To Appear). - Luyu Gao, Aman Madaan, Shuyan Zhou, Uri Alon, Pengfei Liu, Yiming Yang, Jamie Callan, Graham Neubig.
PAL: Program-aided Language Models (BibTex, Code/Data)
International Conference on Machine Learning (ICML). Toron. July 2023 (To Appear). - Junhong Shen, Liam Li, Lucio Dery, Corey Staten, Mikhail Khodak, Graham Neubig, Ameet Talwalkar.
Cross-Modal Fine-Tuning: Align then Refine (BibTex, Code/Data)
International Conference on Machine Learning (ICML). Honolulu, US. July 2023 (To Appear). - Lindia Tjuatja, Emmy Liu, Lori Levin, Graham Neubig.
Syntax and Semantics Meet in the “Middle”: Probing the Syntax-Semantics Interface of LMs Through Agentivity (BibTex)
The Joint Conference on Lexical and Computational Semantics (*SEM). Toronto, Canada. July 2023 (To Appear). - Frank F. Xu, Uri Alon, Graham Neubig.
Why do Nearest Neighbor Language Models Work? (BibTex)
International Conference on Machine Learning (ICML). Honolulu, US. July 2023 (To Appear).
All of my publications can be found on my publications page, and my most highly cited papers can be found on Google Scholar.
Other Links
- Slides for tutorials and classes can be found on my teaching page
- Software and resources that I've developed can be found on my software page.
- Tools for Natural Language Processing
- The Kyoto Free Translation Task: A task that can be used for evaluation of English-Japanese translation systems
- Japanese Parallel Data: A list of various data that can be used to create machine translation systms to/from Japanese