Jason Lee

I am currently a Senior Machine Learning Scientist at Tesla Autopilot.

I obtained a Ph.D in Machine Learning from New York University, where I spent five delightful years training neural networks under the watchful eyes of Kyunghyun Cho.

I hold a BA and an MPhil from the University of Cambridge, and had a few internships at Google AI and Facebook AI Research. I am originally from South Korea, and have lived in the UK, Poland and Switzerland in the past.

Email | CV | Google Scholar | Github | LinkedIn

Papers

Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation
J. Lee, R. Shu and K. Cho
Empirical Methods in Natural Language Processing (EMNLP), 2020
[arxiv] [bib]

On the Discrepancy between Density Estimation and Sequence Generation
J. Lee, D. Tran, O. Firat and K. Cho
Empirical Methods in Natural Language Processing (EMNLP), Workshop on Structured Prediction for NLP, 2020, Oral
[arxiv] [bib]

Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic
Inference using a Delta Posterior
R. Shu, J. Lee, H. Nakayama and K. Cho
AAAI Conference on Artificial Intelligence (AAAI) , 2020
[arxiv] [bib]

Multi-Turn Beam Search for Neural Dialogue Modeling
I. Kulikov*, J. Lee* and K. Cho
Neural Information Processing Systems (NeurIPS), Conversational AI Workshop, 2019, Oral
[arxiv] [bib]

Countering Language Drift via Visual Grounding
J. Lee, K. Cho and D. Kiela
Empirical Methods in Natural Language Processing (EMNLP), 2019
[arxiv] [bib]

Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement
J. Lee*, E. Mansimov* and K. Cho
Empirical Methods in Natural Language Processing (EMNLP), 2018, Oral
[arxiv] [code] [bib]

Emergent Translation in Multi-Agent Communication
J. Lee, K. Cho, J. Weston and D. Kiela
International Conference on Learning Representations (ICLR), 2018
[arxiv] [code] [bib]

Fully Character-Level Neural Machine Translation without Explicit Segmentation
J. Lee, K. Cho and T. Hofmann
Transactions of the Association for Computational Linguistics (TACL), 2017
[arxiv] [journal] [code] [bib]