Yoon Kim
Yoon Kim
MIT-IBM Watson AI Lab
Verified email at seas.harvard.edu - Homepage
Title
Cited by
Cited by
Year
Convolutional Neural Networks for Sentence Classification
Y Kim
EMNLP 2014, 2014
92112014
Character-Aware Neural Language Models
Y Kim, Y Jernite, D Sontag, AM Rush
AAAI 2016, 2015
14372015
OpenNMT: Open-Source Toolkit for Neural Machine Translation
G Klein, Y Kim, Y Deng, J Senellart, AM Rush
ACL 2017 (System Demonstrations), 2017
11542017
Sequence-Level Knowledge Distillation
Y Kim, AM Rush
EMNLP 2016, 2016
3602016
Structured Attention Networks
Y Kim, C Denton, L Hoang, AM Rush
ICLR 2017, 2017
2432017
Temporal Analysis of Language through Neural Language Models
Y Kim, YI Chiu, K Hanaki, D Hegde, S Petrov
Proceedings of the ACL 2014 Workshop on Language Technologies and …, 2014
2212014
Adversarially Regularized Autoencoders
J Zhao, Y Kim, K Zhang, AM Rush, Y LeCun
ICML 2018, 2017
195*2017
Semi-Amortized Variational Autoencoders
Y Kim, S Wiseman, AC Miller, D Sontag, AM Rush
ICML 2018, 2018
1152018
Avoiding Latent Variable Collapse With Generative Skip Models
AB Dieng, Y Kim, AM Rush, DM Blei
AISTATS 2019, 2018
842018
Latent Alignment and Variational Attention
Y Deng, Y Kim, J Chiu, D Guo, AM Rush
NeurIPS 2018, 2018
662018
Adapting Sequence Models for Sentence Correction
A Schmaltz, Y Kim, AM Rush, SM Shieber
EMNLP 2017, 2017
522017
Unsupervised Recurrent Neural Network Grammars
Y Kim, AM Rush, L Yu, A Kuncoro, C Dyer, G Melis
NAACL 2019, 2019
502019
Sentence-Level Grammatical Error Identification as Sequence-to-Sequence Correction
A Schmaltz, Y Kim, AM Rush, SM Shieber
Proceedings of the Eleventh Workshop on Innovative Use of NLP for Building …, 2016
332016
Compound Probabilistic Context-Free Grammars for Grammar Induction
Y Kim, C Dyer, AM Rush
ACL 2019, 2019
322019
A Tutorial on Deep Latent Variable Models of Natural Language
Y Kim, S Wiseman, AM Rush
arXiv preprint arXiv:1812.06834, 2018
242018
Credibility Adjusted Term Frequency: A Supervised Term Weighting Scheme for Sentiment Analysis and Text Classification
Y Kim, O Zhang
Proceedings of the 5th Workshop on Computational Approaches to Subjectivity …, 2014
202014
Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
RD Buhai, Y Halpern, Y Kim, A Risteski, D Sontag
ICML 2020, 2019
62019
Amortized Bethe Free Energy Minimization for Learning MRFs
S Wiseman, Y Kim
NeurIPS 2019, 2019
42019
Deep Latent Variable Models of Natural Language
Y Kim
PhD Thesis, Harvard University, 2020
12020
Sequence-level Mixed Sample Data Augmentation
D Guo, Y Kim, AM Rush
EMNLP 2020, 2020
2020
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Articles 1–20