Sean Welleck's Home Page
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E-mail: wellecks {@ | at} uw.edu
Links: [google scholar][twitter][blog][github]
I am a Postdoctoral Scholar at the University of Washington and Young Investigator at AI2, working with Yejin Choi.
My research focuses on deep learning and structured prediction, with applications in natural language processing.
Previously, I earned a PhD at New York University, advised by Kyunghyun Cho and Zheng Zhang.
News
Papers
- S. Welleck, J. Liu, R. Le Bras, H. Hajishirzi, Y. Choi, K. Cho. NaturalProofs: Mathematical Theorem Proving in Natural Language.
Preprint 2021.
[data/code][project page]
- K. Pillutla, S. Swayamdipta, R. Zellers, J. Thickstun, S. Welleck, Y. Choi, Z. Harchaoui. An Information Divergence Measure Between Neural Text and Human Text.
Preprint 2021.
[code]
- L. Liu, K. Pillutla, S. Welleck, S. Oh, Y. Choi, Z. Harchaoui. Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral.
Preprint 2021.
- I. Kulikov, S. Welleck, K. Cho. Mode recovery in neural autoregressive sequence modeling.
ACL-IJCNLP 5th Workshop on Structured Prediction for NLP (SPNLP) 2021.
[code]
- S. Welleck. Order and Learning in Sequential Neural Structured Prediction.
PhD Thesis, New York University.
[slides]
- S. Welleck, K. Cho. MLE-guided parameter search for task loss minimization in neural sequence modeling.
35th AAAI Conference on Artificial Intelligence (AAAI) 2021.
[code][poster][talk]
- S. Welleck*, I. Kulikov*, J. Kim, R. Pang, K. Cho. Consistency of a Recurrent Language Model With Respect to Incomplete Decoding.
Empirical Methods in Natural Language Processing (EMNLP) 2020.
[code][talk]
- E. Mansimov, A. Wang, S. Welleck, K. Cho. A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models.
arXiv pre-print 2020.
[code]
- M. Li, S. Roller, I. Kulikov, S. Welleck, Y.L. Boureau, K. Cho, J. Weston. Making Inconsistent Dialogue Unlikely with Unlikelihood Training.
58th Annual Meeting of the Association for Computational Linguistics, (ACL) 2020.
- S. Welleck*, I. Kulikov*, S. Roller, E. Dinan, K. Cho, J. Weston. Neural Text Generation with Unlikelihood Training.
8th International Conference on Learning Representations (ICLR) 2020.
[code]
- S. Welleck, K. Brantley, H. Daume III, K. Cho. Non-Monotonic Sequential Text Generation.
36th International Conference on Machine Learning (ICML) 2019.
[code] [slides] [poster]
- S. Welleck, K. Cho. Sequential Graph Dependency Parser.
Recent Advances in Natural Language Processing (RANLP) 2019.
[slides]
- S. Welleck, J. Weston, A. Szlam, K. Cho. Dialogue Natural Language Inference.
57th Annual Meeting of the Association for Computational Linguistics, (ACL) 2019.
[dataset][poster][press]
- S. Welleck, Z. Yao, Y. Gai, J. Mao, Z. Zhang, K. Cho. Loss Functions for Multiset Prediction.
Neural Information Processing Systems 31 (NeurIPS) 2018.
NVIDIA AI Labs Pioneering Research Award 2018.
[poster]
- S. Welleck, J. Mao, K. Cho, Z. Zhang. Saliency-based Sequential Image Attention with Multiset Prediction.
Neural Information Processing Systems 30 (NIPS) 2017.
NVIDIA AI Labs Pioneering Research Award 2017.
[poster][press]
- S. Welleck. Efficient AUC Optimization for Information Ranking Applications.
European Conference on Information Retrieval (ECIR) 2016.
Teaching
- Deep Learning (DS-GA 1008)
New York University
Fall 2020
- Deep Learning for NLP
African Master's Program in Machine Intelligence
March 2020
- Introduction to Machine Learning (CSCI-UA 0473)
New York University
Spring 2020
- NLP with Representation Learning (DS-GA 1011)
New York University
Fall 2019
Past
- Facebook, AI Research Team (FAIR), May. 2019 - Sep. 2019
- Facebook, AI Research Team (FAIR), May. 2018 - Jan. 2019
- Primer AI, Feb. 2016 - Aug. 2016
- IBM, Sep. 2014 - Feb. 2016
- University of Pennsylvania (Computer Science, MSE), May. 2013 - May. 2014
- University of Pennsylvania (Computer Science, BSE), Sep. 2009 - Feb. 2013