Hi, I’m Jon Gauthier. I’m a Ph.D. student in the Department of Brain and
Cognitive Sciences at the Massachusetts Institute of Technology.
I build computational models of how people learn, understand, and produce
language. I collaborate with members of the Computational Psycholinguistics
Laboratory and the Computational Cognitive Science Group, combining
methods from artificial intelligence, linguistics,
neuroscience, and philosophy. I also co-run the Brain and
Cognitive Sciences Philosophy Circle.
Before joining MIT, I did research in natural language processing and machine
learning at Stanford University in the Natural Language Processing
Group, where I was advised by Christopher Manning. I also spent time
as a researcher at OpenAI and Google Brain, where I mainly
collaborated with Ilya Sutskever and Oriol Vinyals.
I had the good fortune to begin research at a young age, thanks to the
generosity and support of my advisors and academic community. I’m interested
in helping ambitious undergraduate students likewise break into the world of
academia. Please get in touch!
Recent personal news
- We’ve just launched LM Zoo, an open source repository of
state-of-the-art neural network language models.
- The Open Philanthropy Project has named me an AI Fellow.
We’ll be collaborating to support the development of more interpretable,
robust systems for language understanding, and the discussion of both short-
and long-term potential risks of artificial intelligence.
- I joined the MIT Department of Brain and Cognitive Sciences in
September 2017.
Research
(Find me on Google Scholar for an up-to-date list.)
A systematic assessment of syntactic generalization in neural language models.
Jennifer Hu, Jon Gauthier, Peng Qian, Ethan Wilcox, and Roger Levy.
ACL 2020.
@inproceedings{hu2020systematic,
author = {Hu, Jennifer and Gauthier, Jon and Qian, Peng and Wilcox, Ethan and Levy, Roger},
title = {A systematic assessment of syntactic generalization in neural language models},
booktitle = {Proceedings of the Association of Computational Linguistics},
year = {2020}
}
From mental representations to neural codes: A multilevel approach.
Jon Gauthier, João Loula, Eli Pollock, Tyler Brooke Wilson, and Catherine Wong.
Behavioral and Brain Sciences.
@article{gauthier2019from,
title={From mental representations to neural codes: A multilevel approach},
volume={42},
DOI={10.1017/S0140525X19001390},
journal={Behavioral and Brain Sciences},
publisher={Cambridge University Press},
author={Gauthier, Jon and Loula, João and Pollock, Eli and Wilson, Tyler Brooke and Wong, Catherine},
year={2019},
pages={e228}
}
Linking human and artificial neural representations of language.
Jon Gauthier and Roger Levy.
EMNLP 2019.
@InProceedings{gauthier2019linking,
author = {Gauthier, Jon and Levy, Roger P.},
title = {Linking human and artificial neural representations of language},
booktitle = {Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing},
month = {November},
year = {2019},
address = {Hong Kong},
publisher = {Association for Computational Linguistics},
}
A rational model of syntactic bootstrapping.
Jon Gauthier, Roger Levy, and Joshua B. Tenenbaum.
Cognitive Science 2019.
@InProceedings{gauthier2019rational,
author = {Gauthier, Jon and Levy, Roger and Tenenbaum, Joshua B.},
title = {A rational model of syntactic bootstrapping},
booktitle = {Proceedings of the 41st Annual Meeting of the Cognitive Science Society},
month = {July},
year = {2019},
address = {Montreal, Canada},
}
Does the brain represent words? An evaluation of brain decoding studies of language understanding.
{Jon Gauthier and Anna Ivanova}.
2018 Conference on Cognitive Computational Neuroscience.
@InProceedings{gauthier2018word,
author = {Gauthier, Jon and Ivanova, Anna},
title = {Does the brain represent words? An evaluation of brain decoding studies of language understanding.},
booktitle = {Proceedings of the 2nd Conference on Cognitive Computational Neuroscience},
month = {September},
year = {2018},
address = {Philadelphia, Pennsylvania}
},
Word learning and the acquisition of syntactic–semantic overhypotheses.
Jon Gauthier, Roger Levy, and Joshua B. Tenenbaum.
Cognitive Science 2018.
@InProceedings{gauthier2018word,
author = {Gauthier, Jon and Levy, Roger and Tenenbaum, Joshua B.},
title = {Word learning and the acquisition of syntactic--semantic overhypotheses},
booktitle = {Proceedings of the 40th Annual Meeting of the Cognitive Science Society},
month = {July},
year = {2018},
address = {Madison, Wisconsin},
}
A paradigm for situated and goal-driven language learning.
Jon Gauthier and Igor Mordatch.
NIPS 2016 Machine Intelligence Workshop.
@misc{1610.03585,
Author = {Jon Gauthier and Igor Mordatch},
Title = {A Paradigm for Situated and Goal-Driven Language Learning},
Year = {2016},
Eprint = {arXiv:1610.03585},
}
A fast unified model for parsing and sentence understanding.
{Sam Bowman, Jon Gauthier}, Raghav Gupta, Abhinav Rastogi, Christopher D. Manning, and Christopher Potts.
ACL 2016.
@InProceedings{bowman2016fast,
author = {Bowman, Samuel R. and Gauthier, Jon and Rastogi, Abhinav and Gupta, Raghav and Manning, Christopher D. and Potts, Christopher},
title = {A Fast Unified Model for Parsing and Sentence Understanding},
booktitle = {Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
month = {August},
year = {2016},
address = {Berlin, Germany},
publisher = {Association for Computational Linguistics},
pages = {1466--1477},
url = {http://www.aclweb.org/anthology/P16-1139}
}
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