Sean J Welleck
Sean J Welleck
Postdoctoral scholar, University of Washington
Verified email at - Homepage
Cited by
Cited by
Neural text generation with unlikelihood training
S Welleck, I Kulikov, S Roller, E Dinan, K Cho, J Weston
International Conference on Learning Representations (ICLR) 2020, 2019
Dialogue natural language inference
S Welleck, J Weston, A Szlam, K Cho
ACL 2019, 2018
Non-Monotonic Sequential Text Generation
S Welleck, K Brantley, H Daumé III, K Cho
International Conference on Machine Learning (ICML) 2019, 2019
Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training
M Li, S Roller, I Kulikov, S Welleck, YL Boureau, K Cho, J Weston
ACL 2020, 2019
A generalized framework of sequence generation with application to undirected sequence models
E Mansimov, A Wang, S Welleck, K Cho
arXiv preprint arXiv:1905.12790, 2019
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding
S Welleck, I Kulikov, J Kim, RY Pang, K Cho
EMNLP 2020, 2020
Saliency-based sequential image attention with multiset prediction
S Welleck, J Mao, K Cho, Z Zhang
NeurIPS 2017, 2017
Loss Functions for Multiset Prediction
S Welleck, Z Yao, Y Gai, J Mao, Z Zhang, K Cho
NeurIPS 2018, 2018
Generating weights for biometric tokens in probabilistic matching systems
M Poplavski, S Schumacher, P Snehal, SJ Welleck, A Xia, Y Zhou
US Patent 9,253,189, 2016
Efficient AUC optimization for information ranking applications
SJ Welleck
European Conference on Information Retrieval (ECIR) 2016, 159-170, 2016
MLE-guided parameter search for task loss minimization in neural sequence modeling
S Welleck, K Cho
AAAI 2021, 2020
NaturalProofs: Mathematical Theorem Proving in Natural Language
S Welleck, J Liu, RL Bras, H Hajishirzi, Y Choi, K Cho
NeurIPS 2021 Datasets & Benchmarks, 2021
Non-monotonic sequential text generation
K Brantley, K Cho, H Daumé III, S Welleck
Proceedings of the 2019 Workshop on Widening NLP, 57-59, 2019
Sequential Graph Dependency Parser
S Welleck, K Cho
Recent Advances in Natural Language Processing (RANLP) 2019, 2019
Symbolic Knowledge Distillation: from General Language Models to Commonsense Models
P West, C Bhagavatula, J Hessel, JD Hwang, L Jiang, RL Bras, X Lu, ...
arXiv preprint arXiv:2110.07178, 2021
Cold Decoding: Constrained Text Generation with Langevin Dynamics
L Qin, S Welleck, D Khashabi, Y Choi
Symbolic Brittleness in Sequence Models: on Systematic Generalization in Symbolic Mathematics
S Welleck, P West, J Cao, Y Choi
arXiv preprint arXiv:2109.13986, 2021
Electronic device for obtaining sentence corresponding to context information and operating method thereof
Y Choi, KIM Jaedeok, I Kulikov, S Welleck, P Yuanzhe, CHO KyungHyun
US Patent App. 17/077,874, 2021
Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral
L Liu, K Pillutla, S Welleck, S Oh, Y Choi, Z Harchaoui
NeurIPS 2021, 2021
Mode recovery in neural autoregressive sequence modeling
I Kulikov, S Welleck, K Cho
SPNLP 2021, 2021
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