Nelson Liu

Nelson Liu

Hi! I recently graduated from the University of Washington, where I received degrees in computer science and linguistics. In Fall 2019, I will start a PhD in computer science at Stanford University.

I work on natural language processing, and I'm particularly interested in understanding and augmenting the generalizability and robustness of natural language processing systems.

Previously, I spent four amazing years as an undergraduate at the University of Washington, where I worked with Noah A. Smith. I've also spent time at the Allen Institute for Artificial Intelligence (AI2) (working with Matt Gardner), and the USC Information Sciences Institute (working with Kevin Knight and Jonathan May).

Thanks to the support of my research mentors, I was fortunate to begin working on research early in my undergraduate career. I’m happy to help ambitious undergraduate students interested in natural language processing or machine learning (especially those at the University of Washington) get started with research—feel free to email me!

Email: nfliu [strudel]

Links: [Full CV] [Twitter] [Github] [Google Scholar] [Blog]

Recent News

  • (5/2019) New paper on fact-aware language modeling accepted to ACL 2019—congratulations to my amazing collaborators!
  • (4/2019) I'll be joining the Stanford Natural Language Processing Group as a computer science PhD student in September 2019.
  • (4/2019) I was fortunate to receive a NSF Graduate Research Fellowship in natural language processing.
  • (2/2019) Two papers accepted to NAACL 2019, preprints below!


  • Barack's Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling
    Robert L. Logan IV, Nelson F. Liu, Matthew E. Peters, Matt Gardner, and Sameer Singh.
    To appear at Annual Meeting of the Association for Computational Linguistics (ACL), 2019.
    [bib] [abstract] [code] [dataset]

  • Linguistic Knowledge and Transferability of Contextual Representations
    Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, and Noah A. Smith.
    In North American Chapter of the Association for Computational Linguistics (NAACL), 2019.
    [bib] [abstract] [slides: pdf, pdf with notes, key] [code]

  • Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets
    Nelson F. Liu, Roy Schwartz, and Noah A. Smith.
    In North American Chapter of the Association for Computational Linguistics (NAACL), 2019.
    [bib] [abstract] [slides: pdf, pdf with notes, key] [code]

  • LSTMs Exploit Linguistic Attributes of Data
    Nelson F. Liu, Omer Levy, Roy Schwartz, Chenhao Tan, and Noah A. Smith.
    In ACL Workshop on Representation Learning for NLP (RepL4NLP), 2018. (Best Paper Award).
    [bib] [abstract] [(short) slides] [poster] [code]

  • AllenNLP: A Deep Semantic Natural Language Processing Platform
    Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew Peters, Michael Schmitz, and Luke Zettlemoyer.
    In ACL Workshop for Natural Language Processing Open Source Software (NLP-OSS), 2018.
    [bib] [abstract] [code]

  • Discovering Phonesthemes with Sparse Regularization
    Nelson F. Liu, Gina-Anne Levow, and Noah A. Smith.
    In NAACL Workshop on Subword and Character Level Models in NLP (SCLeM), 2018.
    [bib] [abstract] [poster] [code]

  • Crowdsourcing Multiple Choice Science Questions
    Johannes Welbl, Nelson F. Liu, and Matt Gardner.
    In EMNLP Workshop on Noisy User-generated Text, 2017.
    [bib] [abstract] [data] [poster]