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Kyunghyun Cho
KyungHyun Cho
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- affiliation: New York University, Courant Institute of Mathematical Sciences
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2020 – today
- 2024
- [j35]Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho:
Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs. Trans. Mach. Learn. Res. 2024 (2024) - [j34]Angelica Chen, Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez:
Learning from Natural Language Feedback. Trans. Mach. Learn. Res. 2024 (2024) - [j33]Nathan H. Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho:
Blind Biological Sequence Denoising with Self-Supervised Set Learning. Trans. Mach. Learn. Res. 2024 (2024) - [j32]Sonia Castelo, João Rulff
, Erin McGowan
: Visualization of AI-Assisted Task Guidance in AR. IEEE Trans. Vis. Comput. Graph. 30(1): 1313-1323 (2024) - [c180]Taeyeon Kim
Holistic Patient Assessment System using Digital Twin for XR Medical Teleconsultation. AHs 2024: 72-78 - [c179]Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston:
Leveraging Implicit Feedback from Deployment Data in Dialogue. EACL (2) 2024: 60-75 - [c178]Weizhe Yuan, Kyunghyun Cho, Jason Weston:
System-Level Natural Language Feedback. EACL (1) 2024: 2773-2789 - [c177]Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L. Leavitt, Naomi Saphra
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs. ICLR 2024 - [c176]Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi:
Protein Discovery with Discrete Walk-Jump Sampling. ICLR 2024 - [c175]Aya Abdelsalam Ismail, Julius Adebayo, Héctor Corrada Bravo, Stephen Ra, Kyunghyun Cho:
Concept Bottleneck Generative Models. ICLR 2024 - [c174]Sungmin Cha, Kyunghyun Cho, Taesup Moon:
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning. ICML 2024 - [c173]Deokjae Lee, Hyun Oh Song, Kyunghyun Cho:
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization. ICML 2024 - [c172]Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho:
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks. ICML 2024 - [c171]Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Xian Li, Sainbayar Sukhbaatar, Jing Xu, Jason Weston:
Self-Rewarding Language Models. ICML 2024 - [c170]Naomi Saphra, Eve Fleisig, Kyunghyun Cho, Adam Lopez:
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models. NAACL-HLT 2024: 2310-2326 - [c169]Nicholas Lourie, Kyunghyun Cho, He He:
Show Your Work with Confidence: Confidence Bands for Tuning Curves. NAACL-HLT 2024: 3455-3472 - [i260]Yatong Bai, Utsav Garg, Apaar Shanker, Haoming Zhang, Samyak Parajuli, Erhan Bas, Isidora Filipovic, Amelia N. Chu, Eugenia D. Fomitcheva, Elliot Branson, Aerin Kim, Somayeh Sojoudi, Kyunghyun Cho:
Let's Go Shopping (LGS) - Web-Scale Image-Text Dataset for Visual Concept Understanding. CoRR abs/2401.04575 (2024) - [i259]Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Sainbayar Sukhbaatar, Jing Xu, Jason Weston:
Self-Rewarding Language Models. CoRR abs/2401.10020 (2024) - [i258]Sungmin Cha, Kyunghyun Cho:
Hyperparameters in Continual Learning: a Reality Check. CoRR abs/2403.09066 (2024) - [i257]Saksham Bassi, Duygu Ataman, Kyunghyun Cho:
Generalization Measures for Zero-Shot Cross-Lingual Transfer. CoRR abs/2404.15928 (2024) - [i256]Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston:
Iterative Reasoning Preference Optimization. CoRR abs/2404.19733 (2024) - [i255]Chaojie Zhang, Shengjia Chen
MR-Transformer: Vision Transformer for Total Knee Replacement Prediction Using Magnetic Resonance Imaging. CoRR abs/2405.02784 (2024) - [i254]Kyunghyun Cho:
A Brief Introduction to Causal Inference in Machine Learning. CoRR abs/2405.08793 (2024) - [i253]Divyam Madaan, Taro Makino, Sumit Chopra, Kyunghyun Cho:
A Framework for Multi-modal Learning: Jointly Modeling Inter- & Intra-Modality Dependencies. CoRR abs/2405.17613 (2024) - [i252]Natasa Tagasovska, Vladimir Gligorijevic, Kyunghyun Cho, Andreas Loukas:
Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient. CoRR abs/2405.18075 (2024) - [i251]Angelica Chen, Sadhika Malladi, Lily H. Zhang, Xinyi Chen, Qiuyi Zhang, Rajesh Ranganath, Kyunghyun Cho:
Preference Learning Algorithms Do Not Learn Preference Rankings. CoRR abs/2405.19534 (2024) - [i250]Siavash Golkar, Alberto Bietti, Mariel Pettee, Michael Eickenberg, Miles D. Cranmer, Keiya Hirashima
Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task. CoRR abs/2406.02585 (2024) - [i249]Haresh Rengaraj Rajamohan, Richard Kijowski, Kyunghyun Cho, Cem M. Deniz:
Modified Risk Formulation for Improving the Prediction of Knee Osteoarthritis Progression. CoRR abs/2406.10119 (2024) - [i248]Deokjae Lee, Hyun Oh Song, Kyunghyun Cho:
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization. CoRR abs/2406.14876 (2024) - [i247]Weizhe Yuan, Ilia Kulikov, Ping Yu, Kyunghyun Cho, Sainbayar Sukhbaatar, Jason Weston, Jing Xu:
Following Length Constraints in Instructions. CoRR abs/2406.17744 (2024) - [i246]Samuel Stanton, Robert Alberstein, Nathan C. Frey, Andrew M. Watkins, Kyunghyun Cho:
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms. CoRR abs/2407.00236 (2024) - [i245]Yeonji Lee, Sangjun Park, Kyunghyun Cho, JinYeong Bak:
MentalAgora: A Gateway to Advanced Personalized Care in Mental Health through Multi-Agent Debating and Attribute Control. CoRR abs/2407.02736 (2024) - [i244]Kyumin Park, Myung Jae Baik, YeongJun Hwang, Yen Shin, HoJae Lee, Ruda Lee, Sang Min Lee, Je Young Hannah Sun, Ah Rah Lee, Si Yeun Yoon, Dong-Ho Lee, Jihyung Moon, JinYeong Bak, Kyunghyun Cho, Jong-Woo Paik, Sungjoon Park:
Harmful Suicide Content Detection. CoRR abs/2407.13942 (2024) - [i243]Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun:
𝕏-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs. CoRR abs/2407.18134 (2024) - [i242]Natasa Tagasovska, Ji Won Park, Matthieu Kirchmeyer, Nathan C. Frey, Andrew Martin Watkins, Aya Abdelsalam Ismail, Arian Rokkum Jamasb, Edith Lee, Tyler Bryson, Stephen Ra, Kyunghyun Cho:
Antibody DomainBed: Out-of-Distribution Generalization in Therapeutic Protein Design. CoRR abs/2407.21028 (2024) - [i241]Yuanqing Wang, Kyunghyun Cho:
Non-convolutional Graph Neural Networks. CoRR abs/2408.00165 (2024) - [i240]Buxin Su, Jiayao Zhang, Natalie Collina, Yuling Yan, Didong Li, Kyunghyun Cho, Jianqing Fan, Aaron Roth, Weijie J. Su:
Analysis of the ICML 2023 Ranking Data: Can Authors' Opinions of Their Own Papers Assist Peer Review in Machine Learning? CoRR abs/2408.13430 (2024) - [i239]Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun, Hyun Oh Song, Kyunghyun Cho:
Targeted Cause Discovery with Data-Driven Learning. CoRR abs/2408.16218 (2024) - [i238]Yuanqing Wang, Kenichiro Takaba, Michael S. Chen, Marcus Wieder, Yuzhi Xu, Tong Zhu, John Z. H. Zhang, Arnav Nagle, Kuang Yu, Xinyan Wang, Daniel J. Cole, Joshua A. Rackers, Kyunghyun Cho, Joe G. Greener, Peter K. Eastman, Stefano Martiniani, Mark E. Tuckerman:
On the design space between molecular mechanics and machine learning force fields. CoRR abs/2409.01931 (2024) - [i237]Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho:
Using Deep Autoregressive Models as Causal Inference Engines. CoRR abs/2409.18581 (2024) - 2023
- [j31]Lavender Yao Jiang, Xujin Chris Liu, Nima Pour Nejatian, Mustafa Nasir-Moin
Health system-scale language models are all-purpose prediction engines. Nat. 619(7969): 357-362 (2023) - [j30]Michael Y. Hu, Angelica Chen, Naomi Saphra, Kyunghyun Cho:
Latent State Models of Training Dynamics. Trans. Mach. Learn. Res. 2023 (2023) - [j29]Taro Makino, Yixin Wang, Krzysztof J. Geras, Kyunghyun Cho:
Detecting incidental correlation in multimodal learning via latent variable modeling. Trans. Mach. Learn. Res. 2023 (2023) - [j28]Nathan H. Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi:
Predicting Out-of-Domain Generalization with Neighborhood Invariance. Trans. Mach. Learn. Res. 2023 (2023) - [c168]Hongyi Zheng, Yixin Zhu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann:
Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section. ACL (student) 2023: 104-108 - [c167]Zihao Yang
Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment. ACL (student) 2023: 109-118 - [c166]Tianxing He, Jingyu Zhang, Tianle Wang, Sachin Kumar, Kyunghyun Cho, James R. Glass, Yulia Tsvetkov:
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. ACL (1) 2023: 12067-12097 - [c165]Hyunjin Kim
A Transformer-based Function Symbol Name Inference Model from an Assembly Language for Binary Reversing. AsiaCCS 2023: 951-965 - [c164]Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan K. Pritchard, Aviv Regev:
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling. CLeaR 2023: 662-691 - [c163]Cal Peyser, Michael Picheny, Kyunghyun Cho, Rohit Prabhavalkar, W. Ronny Huang, Tara N. Sainath:
A Comparison of Semi-Supervised Learning Techniques for Streaming ASR at Scale. ICASSP 2023: 1-5 - [c162]Eugene Choi, Kyunghyun Cho, Cheolhyoung Lee:
A Non-monotonic Self-terminating Language Model. ICLR 2023 - [c161]Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho, João Sedoc, Naomi Saphra
Linear Connectivity Reveals Generalization Strategies. ICLR 2023 - [c160]Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani:
Towards Understanding and Improving GFlowNet Training. ICML 2023: 30956-30975 - [c159]Cal Peyser, Zhong Meng, Rohit Prabhavalkar, Andrew Rosenberg, Tara N. Sainath, Michael Picheny, Kyunghyun Cho, Ke Hu:
Improving Joint Speech-Text Representations Without Alignment. INTERSPEECH 2023: 1354-1358 - [c158]Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. MIDL 2023: 1726-1750 - [c157]Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson:
Protein Design with Guided Discrete Diffusion. NeurIPS 2023 - [c156]Karolis Martinkus, Jan Ludwiczak, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Kyunghyun Cho, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas:
AbDiffuser: full-atom generation of in-vitro functioning antibodies. NeurIPS 2023 - [e5]Andreas Krause, Emma Brunskill, Kyunghyun Cho, Barbara Engelhardt, Sivan Sabato, Jonathan Scarlett:
International Conference on Machine Learning, ICML 2023, 23-29 July 2023, Honolulu, Hawaii, USA. Proceedings of Machine Learning Research 202, PMLR 2023 [contents] - [e4]Burcu Can, Maximilian Mozes, Samuel Cahyawijaya, Naomi Saphra, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Chen Zhao, Isabelle Augenstein, Anna Rogers, Kyunghyun Cho, Edward Grefenstette, Lena Voita:
Proceedings of the 8th Workshop on Representation Learning for NLP, RepL4NLP@ACL 2023, Toronto, Canada, July 13, 2023. Association for Computational Linguistics 2023, ISBN 978-1-959429-77-7 [contents] - [i236]Cal Peyser, W. Ronny Huang, Tara N. Sainath, Rohit Prabhavalkar, Michael Picheny, Kyunghyun Cho:
Dual Learning for Large Vocabulary On-Device ASR. CoRR abs/2301.04327 (2023) - [i235]Cheolhyoung Lee, Kyunghyun Cho:
Unsupervised Learning of Initialization in Deep Neural Networks via Maximum Mean Discrepancy. CoRR abs/2302.04369 (2023) - [i234]Angelica Chen, Jérémy Scheurer, Tomasz Korbak, Jon Ander Campos, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, Ethan Perez:
Improving Code Generation by Training with Natural Language Feedback. CoRR abs/2303.16749 (2023) - [i233]Jérémy Scheurer, Jon Ander Campos, Tomasz Korbak, Jun Shern Chan, Angelica Chen, Kyunghyun Cho, Ethan Perez:
Training Language Models with Language Feedback at Scale. CoRR abs/2303.16755 (2023) - [i232]Cal Peyser, Michael Picheny, Kyunghyun Cho, Rohit Prabhavalkar, W. Ronny Huang, Tara N. Sainath:
A Comparison of Semi-Supervised Learning Techniques for Streaming ASR at Scale. CoRR abs/2304.11053 (2023) - [i231]Max W. Shen, Emmanuel Bengio, Ehsan Hajiramezanali, Andreas Loukas, Kyunghyun Cho, Tommaso Biancalani:
Towards Understanding and Improving GFlowNet Training. CoRR abs/2305.07170 (2023) - [i230]Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho:
Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs. CoRR abs/2305.14279 (2023) - [i229]Nate Gruver, Samuel Stanton, Nathan C. Frey, Tim G. J. Rudner, Isidro Hötzel, Julien Lafrance-Vanasse, Arvind Rajpal, Kyunghyun Cho, Andrew Gordon Wilson:
Protein Design with Guided Discrete Diffusion. CoRR abs/2305.20009 (2023) - [i228]Ji Won Park, Natasa Tagasovska, Michael Maser, Stephen Ra, Kyunghyun Cho:
BOtied: Multi-objective Bayesian optimization with tied multivariate ranks. CoRR abs/2306.00344 (2023) - [i227]Nathan C. Frey, Daniel Berenberg, Karina Zadorozhny, Joseph Kleinhenz, Julien Lafrance-Vanasse, Isidro Hötzel, Yan Wu, Stephen Ra, Richard Bonneau, Kyunghyun Cho, Andreas Loukas, Vladimir Gligorijevic, Saeed Saremi:
Protein Discovery with Discrete Walk-Jump Sampling. CoRR abs/2306.12360 (2023) - [i226]Divyam Madaan, Daniel K. Sodickson, Kyunghyun Cho, Sumit Chopra:
On Sensitivity and Robustness of Normalization Schemes to Input Distribution Shifts in Automatic MR Image Diagnosis. CoRR abs/2306.13276 (2023) - [i225]Weizhe Yuan, Kyunghyun Cho, Jason Weston:
System-Level Natural Language Feedback. CoRR abs/2306.13588 (2023) - [i224]Hongyi Zheng, Yixin Zhu, Lavender Yao Jiang, Kyunghyun Cho, Eric Karl Oermann:
Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section. CoRR abs/2307.07051 (2023) - [i223]Richard Yuanzhe Pang, Stephen Roller, Kyunghyun Cho, He He, Jason Weston:
Leveraging Implicit Feedback from Deployment Data in Dialogue. CoRR abs/2307.14117 (2023) - [i222]Karolis Martinkus, Jan Ludwiczak, Kyunghyun Cho, Wei-Ching Liang, Julien Lafrance-Vanasse, Isidro Hötzel, Arvind Rajpal, Yan Wu, Richard Bonneau, Vladimir Gligorijevic, Andreas Loukas:
AbDiffuser: Full-Atom Generation of In-Vitro Functioning Antibodies. CoRR abs/2308.05027 (2023) - [i221]Cal Peyser, Zhong Meng, Ke Hu, Rohit Prabhavalkar, Andrew Rosenberg, Tara N. Sainath, Michael Picheny, Kyunghyun Cho:
Improving Joint Speech-Text Representations Without Alignment. CoRR abs/2308.06125 (2023) - [i220]Sonia Castelo, João Rulff, Erin McGowan, Bea Steers, Guande Wu, Shaoyu Chen, Irán R. Román, Roque Lopez, Ethan Brewer, Chen Zhao, Jing Qian, Kyunghyun Cho, He He, Qi Sun, Huy T. Vo, Juan Pablo Bello
ARGUS: Visualization of AI-Assisted Task Guidance in AR. CoRR abs/2308.06246 (2023) - [i219]Daniel Jiwoong Im, Kyunghyun Cho:
Active and Passive Causal Inference Learning. CoRR abs/2308.09248 (2023) - [i218]Michael Y. Hu, Angelica Chen, Naomi Saphra, Kyunghyun Cho:
Latent State Models of Training Dynamics. CoRR abs/2308.09543 (2023) - [i217]Nathan Ng, Ji Won Park, Jae Hyeon Lee, Ryan Lewis Kelly, Stephen Ra, Kyunghyun Cho:
Blind Biological Sequence Denoising with Self-Supervised Set Learning. CoRR abs/2309.01670 (2023) - [i216]Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho, Matthew L. Leavitt, Naomi Saphra:
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs. CoRR abs/2309.07311 (2023) - [i215]Siavash Golkar, Mariel Pettee, Michael Eickenberg, Alberto Bietti, Miles D. Cranmer
xVal: A Continuous Number Encoding for Large Language Models. CoRR abs/2310.02989 (2023) - [i214]Michael McCabe, Bruno Régaldo-Saint Blancard, Liam Holden Parker, Ruben Ohana, Miles D. Cranmer
Multiple Physics Pretraining for Physical Surrogate Models. CoRR abs/2310.02994 (2023) - [i213]François Lanusse, Liam Holden Parker, Siavash Golkar, Miles D. Cranmer
AstroCLIP: Cross-Modal Pre-Training for Astronomical Foundation Models. CoRR abs/2310.03024 (2023) - [i212]Won-Ik Cho, Eunjung Cho, Kyunghyun Cho:
PaperCard for Reporting Machine Assistance in Academic Writing. CoRR abs/2310.04824 (2023) - [i211]Naomi Saphra, Eve Fleisig, Kyunghyun Cho, Adam Lopez:
First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models. CoRR abs/2311.05020 (2023) - [i210]Nicholas Lourie, Kyunghyun Cho, He He:
Show Your Work with Confidence: Confidence Bands for Tuning Curves. CoRR abs/2311.09480 (2023) - [i209]Alexander Goldberg, Ivan Stelmakh, Kyunghyun Cho, Alice H. Oh, Alekh Agarwal, Danielle Belgrave, Nihar B. Shah:
Peer Reviews of Peer Reviews: A Randomized Controlled Trial and Other Experiments. CoRR abs/2311.09497 (2023) - [i208]Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson:
Perspectives on the State and Future of Deep Learning - 2023. CoRR abs/2312.09323 (2023) - 2022
- [j27]Ren Yi
NetTIME: a multitask and base-pair resolution framework for improved transcription factor binding site prediction. Bioinform. 38(20): 4762-4770 (2022) - [c155]Junjie Hu, Hiroaki Hayashi, Kyunghyun Cho, Graham Neubig:
DEEP: DEnoising Entity Pre-training for Neural Machine Translation. ACL (1) 2022: 1753-1766 - [c154]Carl Edwards, Tuan Manh Lai, Kevin Ros, Garrett Honke, Kyunghyun Cho, Heng Ji:
Translation between Molecules and Natural Language. EMNLP 2022: 375-413 - [c153]Juhee Son, Jiho Jin, Haneul Yoo, JinYeong Bak, Kyunghyun Cho, Alice Oh:
Translating Hanja Historical Documents to Contemporary Korean and English. EMNLP (Findings) 2022: 1260-1272 - [c152]Hongwei Wang, Weijiang Li, Xiaomeng Jin, Kyunghyun Cho, Heng Ji, Jiawei Han, Martin D. Burke:
Chemical-Reaction-Aware Molecule Representation Learning. ICLR 2022 - [c151]Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, Krzysztof J. Geras:
Characterizing and Overcoming the Greedy Nature of Learning in Multi-modal Deep Neural Networks. ICML 2022: 24043-24055 - [c150]Ilia Kulikov, Maksim Eremeev, Kyunghyun Cho:
Characterizing and addressing the issue of oversmoothing in neural autoregressive sequence modeling. AACL/IJCNLP (1) 2022: 1115-1124 - [c149]Cal Peyser, W. Ronny Huang, Andrew Rosenberg, Tara N. Sainath, Michael Picheny, Kyunghyun Cho:
Towards Disentangled Speech Representations. INTERSPEECH 2022: 3603-3607 - [c148]Haneul Yoo, Jiho Jin, Juhee Son, JinYeong Bak, Kyunghyun Cho, Alice Oh:
HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea. NAACL-HLT (Findings) 2022: 1832-1844 - [c147]Seongjin Shin, Sang-Woo Lee, Hwijeen Ahn, Sungdong Kim, HyoungSeok Kim, Boseop Kim, Kyunghyun Cho, Gichang Lee, Woo-Myoung Park, Jung-Woo Ha, Nako Sung:
On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model. NAACL-HLT 2022: 5168-5186 - [c146]Taro Makino, Krzysztof J. Geras, Kyunghyun Cho:
Generative multitask learning mitigates target-causing confounding. NeurIPS 2022 - [c145]Cal Peyser, W. Ronny Huang, Tara N. Sainath, Rohit Prabhavalkar
Dual Learning for Large Vocabulary On-Device ASR. SLT 2022: 245-251 - [e3]Spandana Gella, He He, Bodhisattwa Prasad Majumder, Burcu Can, Eleonora Giunchiglia, Samuel Cahyawijaya, Sewon Min, Maximilian Mozes, Xiang Lorraine Li, Isabelle Augenstein, Anna Rogers, Kyunghyun Cho, Edward Grefenstette, Laura Rimell, Chris Dyer:
Proceedings of the 7th Workshop on Representation Learning for NLP, RepL4NLP@ACL 2022, Dublin, Ireland, May 26, 2022. Association for Computational Linguistics 2022, ISBN 978-1-955917-48-3 [contents] - [i207]Cinjon Resnick, Or Litany, Amlan Kar, Karsten Kreis, James Lucas, Kyunghyun Cho, Sanja Fidler:
Causal Scene BERT: Improving object detection by searching for challenging groups of data. CoRR abs/2202.03651 (2022) - [i206]Taro Makino, Krzysztof J. Geras, Kyunghyun Cho:
Generative multitask learning mitigates target-causing confounding. CoRR abs/2202.04136 (2022) - [i205]Nan Wu, Stanislaw Jastrzebski, Kyunghyun Cho, Krzysztof J. Geras:
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks. CoRR abs/2202.05306 (2022) - [i204]Vlad Sobal, Alfredo Canziani, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Separating the World and Ego Models for Self-Driving. CoRR abs/2204.07184 (2022) - [i203]Seongjin Shin, Sang-Woo Lee, Hwijeen Ahn, Sungdong Kim, HyoungSeok Kim, Boseop Kim, Kyunghyun Cho, Gichang Lee, Woo-Myoung Park, Jung-Woo Ha
On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model. CoRR abs/2204.13509 (2022) - [i202]Jérémy Scheurer, Jon Ander Campos, Jun Shern Chan, Angelica Chen, Kyunghyun Cho, Ethan Perez:
Learning from Natural Language Feedback. CoRR abs/2204.14146 (2022) - [i201]Daniel Berenberg, Jae Hyeon Lee, Simon Kelow, Ji Won Park, Andrew M. Watkins, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho:
Multi-segment preserving sampling for deep manifold sampler. CoRR abs/2205.04259 (2022) - [i200]Juhee Son, Jiho Jin, Haneul Yoo, JinYeong Bak
Translating Hanja historical documents to understandable Korean and English. CoRR abs/2205.10019 (2022) - [i199]Jeevesh Juneja, Rachit Bansal, Kyunghyun Cho, João Sedoc, Naomi Saphra:
Linear Connectivity Reveals Generalization Strategies. CoRR abs/2205.12411 (2022) - [i198]Ningyuan Huang, Yash R. Deshpande, Yibo Liu, Houda Alberts, Kyunghyun Cho, Clara Vania, Iacer Calixto:
Endowing Language Models with Multimodal Knowledge Graph Representations. CoRR abs/2206.13163 (2022) - [i197]Nathan Ng, Neha Hulkund, Kyunghyun Cho, Marzyeh Ghassemi:
Predicting Out-of-Domain Generalization with Local Manifold Smoothness. CoRR abs/2207.02093 (2022) - [i196]Cal Peyser, W. Ronny Huang, Andrew Rosenberg, Tara N. Sainath, Michael Picheny, Kyunghyun Cho:
Towards Disentangled Speech Representations. CoRR abs/2208.13191 (2022) - [i195]Eugene Choi, Cheolhyoung Lee, Kyunghyun Cho:
A Non-monotonic Self-terminating Language Model. CoRR abs/2210.00660 (2022) - [i194]Ji Won Park, Samuel Stanton, Saeed Saremi, Andrew M. Watkins, Henri Dwyer, Vladimir Gligorijevic, Richard Bonneau, Stephen Ra, Kyunghyun Cho:
PropertyDAG: Multi-objective Bayesian optimization of partially ordered, mixed-variable properties for biological sequence design. CoRR abs/2210.04096 (2022) - [i193]Haneul Yoo, Jiho Jin, Juhee Son, JinYeong Bak
HUE: Pretrained Model and Dataset for Understanding Hanja Documents of Ancient Korea. CoRR abs/2210.05112 (2022) - [i192]Natasa Tagasovska, Nathan C. Frey, Andreas Loukas, Isidro Hötzel, Julien Lafrance-Vanasse, Ryan Lewis Kelly, Yan Wu, Arvind Rajpal, Richard Bonneau, Kyunghyun Cho, Stephen Ra, Vladimir Gligorijevic:
A Pareto-optimal compositional energy-based model for sampling and optimization of protein sequences. CoRR abs/2210.10838 (2022) - [i191]Romain Lopez, Natasa Tagasovska, Stephen Ra, Kyunghyun Cho, Jonathan K. Pritchard, Aviv Regev:
Learning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling. CoRR abs/2211.03553 (2022) - [i190]Grace Yang, Ming Cao, Lavender Y. Jiang, Xujin Chris Liu, Alexander T. M. Cheung, Hannah Weiss, David Kurland, Kyunghyun Cho, Eric K. Oermann:
Language Model Classifier Aligns Better with Physician Word Sensitivity than XGBoost on Readmission Prediction. CoRR abs/2211.07047 (2022) - [i189]Vlad Sobal, Jyothir S. V, Siddhartha Jalagam, Nicolas Carion, Kyunghyun Cho, Yann LeCun:
Joint Embedding Predictive Architectures Focus on Slow Features. CoRR abs/2211.10831 (2022) - [i188]Tianxing He, Jingyu Zhang, Tianle Wang, Sachin Kumar, Kyunghyun Cho, James R. Glass, Yulia Tsvetkov:
On the Blind Spots of Model-Based Evaluation Metrics for Text Generation. CoRR abs/2212.10020 (2022) - [i187]Sang-Woo Lee, Sungdong Kim, Donghyeon Ko, Donghoon Ham, Youngki Hong, Shin Ah Oh, Hyunhoon Jung, Wangkyo Jung, Kyunghyun Cho, Dong-Hyun Kwak, Hyungsuk Noh, Woo-Myoung Park:
Can Current Task-oriented Dialogue Models Automate Real-world Scenarios in the Wild? CoRR abs/2212.10504 (2022) - 2021
- [j26]Meet Barot
NetQuilt: deep multispecies network-based protein function prediction using homology-informed network similarity. Bioinform. 37(16): 2414-2422 (2021) - [j25]Nan Wu
Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms. J. Digit. Imaging 34(6): 1414-1423 (2021) - [j24]Yiqiu Shen
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. Medical Image Anal. 68: 101908 (2021) - [j23]Andreas Tjärnberg
Optimal tuning of weighted kNN- and diffusion-based methods for denoising single cell genomics data. PLoS Comput. Biol. 17(1) (2021) - [c144]Sean Welleck, Kyunghyun Cho:
MLE-Guided Parameter Search for Task Loss Minimization in Neural Sequence Modeling. AAAI 2021: 14032-14040 - [c143]Clara Vania, Phu Mon Htut, William Huang, Dhara A. Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, Samuel R. Bowman:
Comparing Test Sets with Item Response Theory. ACL/IJCNLP (1) 2021: 1141-1158 - [c142]Gyuwan Kim, Kyunghyun Cho:
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search. ACL/IJCNLP (1) 2021: 6501-6511 - [c141]Ilia Kulikov, Sean Welleck, Kyunghyun Cho:
Mode recovery in neural autoregressive sequence modeling. SPNLP@ACL-IJCNLP 2021: 44-52 - [c140]Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, Iryna Gurevych:
AdapterFusion: Non-Destructive Task Composition for Transfer Learning. EACL 2021: 487-503 - [c139]Tianxing He, Jun Liu, Kyunghyun Cho, Myle Ott, Bing Liu, James R. Glass, Fuchun Peng:
Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models. EACL 2021: 1121-1133 - [c138]Manling Li, Sha Li, Zhenhailong Wang, Lifu Huang, Kyunghyun Cho, Heng Ji, Jiawei Han, Clare R. Voss:
The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction. EMNLP (1) 2021: 5203-5215 - [c137]Cinjon Resnick, Or Litany, Amlan Kar, Karsten Kreis, James Lucas, Kyunghyun Cho, Sanja Fidler:
Causal BERT: Improving object detection by searching for challenging groups. ICCVW 2021: 2972-2981 - [c136]Shuhei Kurita, Kyunghyun Cho:
Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule. ICLR 2021 - [c135]Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras:
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization. ICML 2021: 4772-4784 - [c134]Ethan Perez, Douwe Kiela, Kyunghyun Cho:
Rissanen Data Analysis: Examining Dataset Characteristics via Description Length. ICML 2021: 8500-8513 - [c133]Sungjoon Park, Jihyung Moon, Sungdong Kim, Won-Ik Cho, Jiyoon Han, Jangwon Park, Chisung Song, Junseong Kim, Youngsook Song, Tae Hwan Oh, Joohong Lee, Juhyun Oh, Sungwon Lyu, Younghoon Jeong, Inkwon Lee, Sangwoo Seo, Dongjun Lee, Hyunwoo Kim, Myeonghwa Lee, Seongbo Jang, Seungwon Do, Sunkyoung Kim, Kyungtae Lim, Jongwon Lee, Kyumin Park, Jamin Shin, Seonghyun Kim, Eunjeong Lucy Park, Alice Oh, Jung-Woo Ha, Kyunghyun Cho:
KLUE: Korean Language Understanding Evaluation. NeurIPS Datasets and Benchmarks 2021 - [c132]Ethan Perez, Douwe Kiela, Kyunghyun Cho:
True Few-Shot Learning with Language Models. NeurIPS 2021: 11054-11070 - [c131]Sean Welleck, Jiacheng Liu, Ronan Le Bras, Hanna Hajishirzi, Yejin Choi, Kyunghyun Cho:
NaturalProofs: Mathematical Theorem Proving in Natural Language. NeurIPS Datasets and Benchmarks 2021 - [c130]Hyojung Han, Seokchan Ahn, Yoonjung Choi, Insoo Chung, Sangha Kim, Kyunghyun Cho:
Monotonic Simultaneous Translation with Chunk-wise Reordering and Refinement. WMT@EMNLP 2021: 1110-1123 - [i186]Cinjon Resnick, Or Litany, Cosmas Heiß, Hugo Larochelle, Joan Bruna, Kyunghyun Cho:
Self-Supervised Equivariant Scene Synthesis from Video. CoRR abs/2102.00863 (2021) - [i185]Daniel Jiwoong Im, Cristina Savin, Kyunghyun Cho:
Online hyperparameter optimization by real-time recurrent learning. CoRR abs/2102.07813 (2021) - [i184]Ethan Perez, Douwe Kiela, Kyunghyun Cho:
Rissanen Data Analysis: Examining Dataset Characteristics via Description Length. CoRR abs/2103.03872 (2021) - [i183]Sean Welleck, Jiacheng Liu, Ronan Le Bras, Hannaneh Hajishirzi, Yejin Choi, Kyunghyun Cho:
NaturalProofs: Mathematical Theorem Proving in Natural Language. CoRR abs/2104.01112 (2021) - [i182]Manling Li, Sha Li, Zhenhailong Wang, Lifu Huang, Kyunghyun Cho, Heng Ji, Jiawei Han, Clare R. Voss:
Future is not One-dimensional: Graph Modeling based Complex Event Schema Induction for Event Prediction. CoRR abs/2104.06344 (2021) - [i181]Sungjoon Park, Jihyung Moon, Sungdong Kim, Won-Ik Cho, Jiyoon Han, Jangwon Park, Chisung Song, Junseong Kim, Yongsook Song, Tae Hwan Oh, Joohong Lee, Juhyun Oh, Sungwon Lyu, Younghoon Jeong, Inkwon Lee, Sangwoo Seo, Dongjun Lee, Hyunwoo Kim, Myeonghwa Lee, Seongbo Jang, Seungwon Do, Sunkyoung Kim, Kyungtae Lim, Jongwon Lee, Kyumin Park, Jamin Shin, Seonghyun Kim, Eunjeong Lucy Park, Alice Oh, Jung-Woo Ha, Kyunghyun Cho:
KLUE: Korean Language Understanding Evaluation. CoRR abs/2105.09680 (2021) - [i180]Ethan Perez, Douwe Kiela, Kyunghyun Cho:
True Few-Shot Learning with Language Models. CoRR abs/2105.11447 (2021) - [i179]Clara Vania, Phu Mon Htut, William Huang, Dhara A. Mungra, Richard Yuanzhe Pang, Jason Phang, Haokun Liu, Kyunghyun Cho, Samuel R. Bowman:
Comparing Test Sets with Item Response Theory. CoRR abs/2106.00840 (2021) - [i178]Ilia Kulikov, Sean Welleck, Kyunghyun Cho:
Mode recovery in neural autoregressive sequence modeling. CoRR abs/2106.05459 (2021) - [i177]William Falcon, Ananya Harsh Jha, Teddy Koker, Kyunghyun Cho:
AAVAE: Augmentation-Augmented Variational Autoencoders. CoRR abs/2107.12329 (2021) - [i176]Benjamin Stadnick, Jan Witowski, Vishwaesh Rajiv, Jakub Chledowski, Farah E. Shamout, Kyunghyun Cho, Krzysztof J. Geras:
Meta-repository of screening mammography classifiers. CoRR abs/2108.04800 (2021) - [i175]Tianxing He, Kyunghyun Cho, James R. Glass:
An Empirical Study on Few-shot Knowledge Probing for Pretrained Language Models. CoRR abs/2109.02772 (2021) - [i174]Annika Brundyn, Jesse Swanson, Kyunghyun Cho, Doug Kondziolka, Eric K. Oermann:
Stereo Video Reconstruction Without Explicit Depth Maps for Endoscopic Surgery. CoRR abs/2109.08227 (2021) - [i173]Hongwei Wang, Weijiang Li, Xiaomeng Jin, Kyunghyun Cho, Heng Ji, Jiawei Han, Martin D. Burke:
Chemical-Reaction-Aware Molecule Representation Learning. CoRR abs/2109.09888 (2021) - [i172]Hyojung Han, Seokchan Ahn, Yoonjung Choi, Insoo Chung, Sangha Kim, Kyunghyun Cho:
Monotonic Simultaneous Translation with Chunk-wise Reordering and Refinement. CoRR abs/2110.09646 (2021) - [i171]Iddo Drori, Yamuna Krishnamurthy, Rémi Rampin, Raoni de Paula Lourenço, Jorge Piazentin Ono, Kyunghyun Cho, Cláudio T. Silva, Juliana Freire:
AlphaD3M: Machine Learning Pipeline Synthesis. CoRR abs/2111.02508 (2021) - [i170]Junjie Hu, Hiroaki Hayashi, Kyunghyun Cho, Graham Neubig:
DEEP: DEnoising Entity Pre-training for Neural Machine Translation. CoRR abs/2111.07393 (2021) - [i169]Daniel Jiwoong Im, Kyunghyun Cho, Narges Razavian:
Causal Effect Variational Autoencoder with Uniform Treatment. CoRR abs/2111.08656 (2021) - [i168]Richard Yuanzhe Pang, He He, Kyunghyun Cho:
Amortized Noisy Channel Neural Machine Translation. CoRR abs/2112.08670 (2021) - [i167]Ilia Kulikov, Maksim Eremeev, Kyunghyun Cho:
Characterizing and addressing the issue of oversmoothing in neural autoregressive sequence modeling. CoRR abs/2112.08914 (2021) - [i166]Yekyung Kim, Seohyeong Jeong, Kyunghyun Cho:
LINDA: Unsupervised Learning to Interpolate in Natural Language Processing. CoRR abs/2112.13969 (2021) - 2020
- [j22]Konrad Zolna, Krzysztof J. Geras, Kyunghyun Cho:
Classifier-agnostic saliency map extraction. Comput. Vis. Image Underst. 196: 102969 (2020) - [j21]Owen Marschall, Kyunghyun Cho, Cristina Savin:
A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks. J. Mach. Learn. Res. 21: 135:1-135:34 (2020) - [j20]John E. Ortega
Neural machine translation with a polysynthetic low resource language. Mach. Transl. 34(4): 325-346 (2020) - [j19]Rodrigo Frassetto Nogueira
Navigation-based candidate expansion and pretrained language models for citation recommendation. Scientometrics 125(3): 3001-3016 (2020) - [j18]Nan Wu
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. IEEE Trans. Medical Imaging 39(4): 1184-1194 (2020) - [c129]Katharina Kann, Samuel R. Bowman, Kyunghyun Cho:
Learning to Learn Morphological Inflection for Resource-Poor Languages. AAAI 2020: 8058-8065 - [c128]Raphael Shu, Jason Lee, Hideki Nakayama
Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior. AAAI 2020: 8846-8853 - [c127]Changhan Wang, Kyunghyun Cho, Jiatao Gu:
Neural Machine Translation with Byte-Level Subwords. AAAI 2020: 9154-9160 - [c126]Margaret Li, Stephen Roller, Ilia Kulikov, Sean Welleck, Y-Lan Boureau, Kyunghyun Cho, Jason Weston:
Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training. ACL 2020: 4715-4728 - [c125]Alex Wang, Kyunghyun Cho, Mike Lewis:
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries. ACL 2020: 5008-5020 - [c124]Jason Lee, Dustin Tran, Orhan Firat, Kyunghyun Cho:
On the Discrepancy between Density Estimation and Sequence Generation. SPNLP@EMNLP 2020: 84-94 - [c123]Sébastien Jean, Kyunghyun Cho:
Log-Linear Reformulation of the Noisy Channel Model for Document-Level Neural Machine Translation. SPNLP@EMNLP 2020: 95-101 - [c122]Cinjon Resnick, Abhinav Gupta, Jakob N. Foerster, Andrew M. Dai, Kyunghyun Cho:
Capacity, Bandwidth, and Compositionality in Emergent Language Learning. AAMAS 2020: 1125-1133 - [c121]Rodrigo Frassetto Nogueira, Zhiying Jiang, Kyunghyun Cho, Jimmy Lin:
Evaluating Pretrained Transformer Models for Citation Recommendation. BIR@ECIR 2020: 89-100 - [c120]Jon Ander Campos, Kyunghyun Cho, Arantxa Otegi
Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning. COLING 2020: 2561-2571 - [c119]António Góis, Kyunghyun Cho, André F. T. Martins:
Learning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings. EAMT 2020: 205-214 - [c118]Edwin Zhang, Nikhil Gupta, Raphael Tang, Xiao Han, Ronak Pradeep, Kuang Lu, Yue Zhang, Rodrigo Frassetto Nogueira, Kyunghyun Cho, Hui Fang
Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset. SDP@EMNLP 2020: 31-41 - [c117]Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, Aishwarya Kamath, Ivan Vulic, Sebastian Ruder, Kyunghyun Cho, Iryna Gurevych:
AdapterHub: A Framework for Adapting Transformers. EMNLP (Demos) 2020: 46-54 - [c116]Manling Li, Qi Zeng
Connecting the Dots: Event Graph Schema Induction with Path Language Modeling. EMNLP (1) 2020: 684-695 - [c115]Jason Lee, Raphael Shu, Kyunghyun Cho:
Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation. EMNLP (1) 2020: 1006-1015 - [c114]Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi:
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. EMNLP (1) 2020: 1268-1283 - [c113]Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho:
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. EMNLP (1) 2020: 5553-5568 - [c112]Ethan Perez, Patrick S. H. Lewis
Unsupervised Question Decomposition for Question Answering. EMNLP (1) 2020: 8864-8880 - [c111]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. ICLR 2020 - [c110]Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang:
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models. ICLR 2020 - [c109]Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston:
Neural Text Generation With Unlikelihood Training. ICLR 2020 - [c108]William F. Whitney, Rajat Agarwal, Kyunghyun Cho, Abhinav Gupta:
Dynamics-Aware Embeddings. ICLR 2020 - [c107]Moin Nadeem, Tianxing He, Kyunghyun Cho, James R. Glass:
A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation. AACL/IJCNLP 2020: 334-346 - [c106]Bofei Zhang, Jimin Tan, Kyunghyun Cho, Gregory Chang, Cem M. Deniz:
Attention-based CNN for KL Grade Classification: Data from the Osteoarthritis Initiative. ISBI 2020: 731-735 - [c105]Jimin Tan, Bofei Zhang, Kyunghyun Cho, Gregory Chang, Cem M. Deniz:
Semi-supervised learning for predicting total knee replacement with unsupervised data augmentation. Medical Imaging: Computer-Aided Diagnosis 2020 - [c104]Nan Wu, Stanislaw Jastrzebski, Jungkyu Park, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras:
Improving the Ability of Deep Neural Networks to Use Information from Multiple Views in Breast Cancer Screening. MIDL 2020: 827-842 - [c103]Abhinav Gupta, Cinjon Resnick, Jakob N. Foerster, Andrew M. Dai, Kyunghyun Cho:
Compositionality and Capacity in Emergent Languages. RepL4NLP@ACL 2020: 34-38 - [i165]Rodrigo Frassetto Nogueira, Zhiying Jiang, Kyunghyun Cho, Jimmy Lin:
Navigation-Based Candidate Expansion and Pretrained Language Models for Citation Recommendation. CoRR abs/2001.08687 (2020) - [i164]Sean Welleck, Ilia Kulikov, Jaedeok Kim, Richard Yuanzhe Pang, Kyunghyun Cho:
Consistency of a Recurrent Language Model With Respect to Incomplete Decoding. CoRR abs/2002.02492 (2020) - [i163]Jason Lee, Dustin Tran, Orhan Firat, Kyunghyun Cho:
On the Discrepancy between Density Estimation and Sequence Generation. CoRR abs/2002.07233 (2020) - [i162]Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. CoRR abs/2002.07613 (2020) - [i161]Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort, Devansh Arpit, Jacek Tabor, Kyunghyun Cho, Krzysztof J. Geras:
The Break-Even Point on Optimization Trajectories of Deep Neural Networks. CoRR abs/2002.09572 (2020) - [i160]Ethan Perez, Patrick S. H. Lewis, Wen-tau Yih, Kyunghyun Cho, Douwe Kiela:
Unsupervised Question Decomposition for Question Answering. CoRR abs/2002.09758 (2020) - [i159]Witold Oleszkiewicz, Taro Makino, Stanislaw Jastrzebski, Tomasz Trzcinski, Linda Moy
Understanding the robustness of deep neural network classifiers for breast cancer screening. CoRR abs/2003.10041 (2020) - [i158]Alex Wang, Kyunghyun Cho, Mike Lewis:
Asking and Answering Questions to Evaluate the Factual Consistency of Summaries. CoRR abs/2004.04228 (2020) - [i157]Edwin Zhang, Nikhil Gupta, Rodrigo Frassetto Nogueira, Kyunghyun Cho, Jimmy Lin:
Rapidly Deploying a Neural Search Engine for the COVID-19 Open Research Dataset: Preliminary Thoughts and Lessons Learned. CoRR abs/2004.05125 (2020) - [i156]Raphael Tang, Rodrigo Frassetto Nogueira, Edwin Zhang, Nikhil Gupta, Phuong Cam, Kyunghyun Cho, Jimmy Lin:
Rapidly Bootstrapping a Question Answering Dataset for COVID-19. CoRR abs/2004.11339 (2020) - [i155]Katharina Kann, Samuel R. Bowman, Kyunghyun Cho:
Learning to Learn Morphological Inflection for Resource-Poor Languages. CoRR abs/2004.13304 (2020) - [i154]António Góis, Kyunghyun Cho, André F. T. Martins:
Learning Non-Monotonic Automatic Post-Editing of Translations from Human Orderings. CoRR abs/2004.14120 (2020) - [i153]Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé
AdapterFusion: Non-Destructive Task Composition for Transfer Learning. CoRR abs/2005.00247 (2020) - [i152]Sean Welleck, Kyunghyun Cho:
MLE-guided parameter search for task loss minimization in neural sequence modeling. CoRR abs/2006.03158 (2020) - [i151]Jonas Pfeiffer, Andreas Rücklé
AdapterHub: A Framework for Adapting Transformers. CoRR abs/2007.07779 (2020) - [i150]Edwin Zhang, Nikhil Gupta, Raphael Tang, Xiao Han, Ronak Pradeep, Kuang Lu, Yue Zhang, Rodrigo Frassetto Nogueira, Kyunghyun Cho, Hui Fang, Jimmy Lin:
Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset. CoRR abs/2007.07846 (2020) - [i149]Houda Alberts, Teresa Huang, Yash Deshpande, Yibo Liu, Kyunghyun Cho, Clara Vania, Iacer Calixto:
VisualSem: a high-quality knowledge graph for vision and language. CoRR abs/2008.09150 (2020) - [i148]William Falcon, Kyunghyun Cho:
A Framework For Contrastive Self-Supervised Learning And Designing A New Approach. CoRR abs/2009.00104 (2020) - [i147]Jason Lee, Raphael Shu, Kyunghyun Cho:
Iterative Refinement in the Continuous Space for Non-Autoregressive Neural Machine Translation. CoRR abs/2009.07177 (2020) - [i146]Moin Nadeem, Tianxing He, Kyunghyun Cho, James R. Glass:
A Systematic Characterization of Sampling Algorithms for Open-ended Language Generation. CoRR abs/2009.07243 (2020) - [i145]William F. Whitney, Min Jae Song, David Brandfonbrener, Jaan Altosaar, Kyunghyun Cho:
Evaluating representations by the complexity of learning low-loss predictors. CoRR abs/2009.07368 (2020) - [i144]Shuhei Kurita, Kyunghyun Cho:
Generative Language-Grounded Policy in Vision-and-Language Navigation with Bayes' Rule. CoRR abs/2009.07783 (2020) - [i143]Nan Wu, Zhe Huang, Yiqiu Shen, Jungkyu Park
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms. CoRR abs/2009.09282 (2020) - [i142]Nathan Ng, Kyunghyun Cho, Marzyeh Ghassemi:
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness. CoRR abs/2009.10195 (2020) - [i141]Gyuwan Kim, Kyunghyun Cho:
Length-Adaptive Transformer: Train Once with Length Drop, Use Anytime with Search. CoRR abs/2010.07003 (2020) - [i140]Jon Ander Campos, Kyunghyun Cho, Arantxa Otegi, Aitor Soroa, Gorka Azkune, Eneko Agirre:
Improving Conversational Question Answering Systems after Deployment using Feedback-Weighted Learning. CoRR abs/2011.00615 (2020) - [i139]Cinjon Resnick, Or Litany, Hugo Larochelle, Joan Bruna, Kyunghyun Cho:
Learned Equivariant Rendering without Transformation Supervision. CoRR abs/2011.05787 (2020) - [i138]Taro Makino, Stanislaw Jastrzebski, Witold Oleszkiewicz, Celin Chacko, Robin Ehrenpreis, Naziya Samreen, Chloe Chhor, Eric Kim, Jiyon Lee, Kristine Pysarenko, Beatriu Reig, Hildegard Toth, Divya Awal, Linda Du, Alice Kim, James Park, Daniel K. Sodickson, Laura Heacock, Linda Moy
Differences between human and machine perception in medical diagnosis. CoRR abs/2011.14036 (2020) - [i137]Elham J. Barezi, Iacer Calixto, Kyunghyun Cho, Pascale Fung:
A Study on the Autoregressive and non-Autoregressive Multi-label Learning. CoRR abs/2012.01711 (2020) - [i136]Stanislaw Jastrzebski, Devansh Arpit, Oliver Åstrand, Giancarlo Kerg, Huan Wang, Caiming Xiong, Richard Socher, Kyunghyun Cho, Krzysztof J. Geras:
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization. CoRR abs/2012.14193 (2020)
2010 – 2019
- 2019
- [j17]Seokho Kang
Conditional Molecular Design with Deep Generative Models. J. Chem. Inf. Model. 59(1): 43-52 (2019) - [j16]Jiatao Gu, Qi Liu, Kyunghyun Cho:
Insertion-based Decoding with Automatically Inferred Generation Order. Trans. Assoc. Comput. Linguistics 7: 661-676 (2019) - [c102]Konrad Zolna, Krzysztof J. Geras, Kyunghyun Cho:
Classifier-Agnostic Saliency Map Extraction. AAAI 2019: 10087-10088 - [c101]Jiatao Gu, Yong Wang, Kyunghyun Cho, Victor O. K. Li:
Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations. ACL (1) 2019: 1258-1268 - [c100]Raphael Shu, Hideki Nakayama
Generating Diverse Translations with Sentence Codes. ACL (1) 2019: 1823-1827 - [c99]Sean Welleck, Jason Weston, Arthur Szlam, Kyunghyun Cho:
Dialogue Natural Language Inference. ACL (1) 2019: 3731-3741 - [c98]Katharina Kann, Anhad Mohananey, Samuel R. Bowman, Kyunghyun Cho:
Neural Unsupervised Parsing Beyond English. DeepLo@EMNLP-IJCNLP 2019: 209-218 - [c97]Kianté Brantley, Kyunghyun Cho, Hal Daumé III, Sean Welleck:
Non-Monotonic Sequential Text Generation. WNLP@ACL 2019: 57-59 - [c96]Jake Zhao, Kyunghyun Cho:
Retrieval-Augmented Convolutional Neural Networks Against Adversarial Examples. CVPR 2019: 11563-11571 - [c95]Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho:
Finding Generalizable Evidence by Learning to Convince Q&A Models. EMNLP/IJCNLP (1) 2019: 2402-2411 - [c94]Katharina Kann, Kyunghyun Cho, Samuel R. Bowman:
Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set. EMNLP/IJCNLP (1) 2019: 3340-3347 - [c93]Laura Graesser, Kyunghyun Cho, Douwe Kiela:
Emergent Linguistic Phenomena in Multi-Agent Communication Games. EMNLP/IJCNLP (1) 2019: 3698-3708 - [c92]Jason Lee, Kyunghyun Cho, Douwe Kiela:
Countering Language Drift via Visual Grounding. EMNLP/IJCNLP (1) 2019: 4384-4394 - [c91]Xiaodong Gu, Kyunghyun Cho, Jung-Woo Ha, Sunghun Kim:
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder. ICLR (Poster) 2019 - [c90]Sean Welleck, Kianté Brantley, Hal Daumé III, Kyunghyun Cho:
Non-Monotonic Sequential Text Generation. ICML 2019: 6716-6726 - [c89]Ilia Kulikov, Alexander H. Miller, Kyunghyun Cho, Jason Weston:
Importance of Search and Evaluation Strategies in Neural Dialogue Modeling. INLG 2019: 76-87 - [c88]Keunwoo Choi, Kyunghyun Cho:
Deep Unsupervised Drum Transcription. ISMIR 2019: 183-191 - [c87]Yiqiu Shen
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening. MLMI@MICCAI 2019: 18-26 - [c86]Nishant Subramani, Samuel R. Bowman, Kyunghyun Cho:
Can Unconditional Language Models Recover Arbitrary Sentences? NeurIPS 2019: 15232-15242 - [c85]Sean Welleck, Kyunghyun Cho:
Sequential Graph Dependency Parser. RANLP 2019: 1338-1345 - [i135]Rodrigo Frassetto Nogueira, Kyunghyun Cho:
Passage Re-ranking with BERT. CoRR abs/1901.04085 (2019) - [i134]Laura Graesser, Kyunghyun Cho, Douwe Kiela:
Emergent Linguistic Phenomena in Multi-Agent Communication Games. CoRR abs/1901.08706 (2019) - [i133]Jiatao Gu, Qi Liu, Kyunghyun Cho:
Insertion-based Decoding with automatically Inferred Generation Order. CoRR abs/1902.01370 (2019) - [i132]Sean Welleck, Kianté Brantley, Hal Daumé III, Kyunghyun Cho:
Non-Monotonic Sequential Text Generation. CoRR abs/1902.02192 (2019) - [i131]Alex Wang, Kyunghyun Cho:
BERT has a Mouth, and It Must Speak: BERT as a Markov Random Field Language Model. CoRR abs/1902.04094 (2019) - [i130]Mate Kisantal, Zbigniew Wojna, Jakub Murawski, Jacek Naruniec, Kyunghyun Cho:
Augmentation for small object detection. CoRR abs/1902.07296 (2019) - [i129]Siavash Golkar, Michael Kagan, Kyunghyun Cho:
Continual Learning via Neural Pruning. CoRR abs/1903.04476 (2019) - [i128]Sébastien Jean, Kyunghyun Cho:
Context-Aware Learning for Neural Machine Translation. CoRR abs/1903.04715 (2019) - [i127]Nan Wu, Jason Phang, Jungkyu Park
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. CoRR abs/1903.08297 (2019) - [i126]Elman Mansimov, Omar Mahmood, Seokho Kang, Kyunghyun Cho:
Molecular geometry prediction using a deep generative graph neural network. CoRR abs/1904.00314 (2019) - [i125]Rodrigo Frassetto Nogueira, Wei Yang, Jimmy Lin, Kyunghyun Cho:
Document Expansion by Query Prediction. CoRR abs/1904.08375 (2019) - [i124]Jihun Oh, Kyunghyun Cho, Joan Bruna:
Advancing GraphSAGE with A Data-Driven Node Sampling. CoRR abs/1904.12935 (2019) - [i123]Siavash Golkar, Kyunghyun Cho:
Task-Driven Data Verification via Gradient Descent. CoRR abs/1905.05843 (2019) - [i122]Iddo Drori, Yamuna Krishnamurthy, Raoni Lourenço, Rémi Rampin
Automatic Machine Learning by Pipeline Synthesis using Model-Based Reinforcement Learning and a Grammar. CoRR abs/1905.10345 (2019) - [i121]Sean Welleck, Kyunghyun Cho:
Sequential Graph Dependency Parser. CoRR abs/1905.10930 (2019) - [i120]Owen Marschall, Kyunghyun Cho, Cristina Savin:
Using local plasticity rules to train recurrent neural networks. CoRR abs/1905.12100 (2019) - [i119]Elman Mansimov, Alex Wang, Kyunghyun Cho:
A Generalized Framework of Sequence Generation with Application to Undirected Sequence Models. CoRR abs/1905.12790 (2019) - [i118]Ilia Kulikov, Jason Lee, Kyunghyun Cho:
Multi-Turn Beam Search for Neural Dialogue Modeling. CoRR abs/1906.00141 (2019) - [i117]Jiatao Gu, Yong Wang, Kyunghyun Cho, Victor O. K. Li:
Improved Zero-shot Neural Machine Translation via Ignoring Spurious Correlations. CoRR abs/1906.01181 (2019) - [i116]Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Sungheon Gene Kim, Linda Moy
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening. CoRR abs/1906.02846 (2019) - [i115]Keunwoo Choi, Kyunghyun Cho:
Deep Unsupervised Drum Transcription. CoRR abs/1906.03697 (2019) - [i114]Owen Marschall, Kyunghyun Cho, Cristina Savin:
A Unified Framework of Online Learning Algorithms for Training Recurrent Neural Networks. CoRR abs/1907.02649 (2019) - [i113]Nishant Subramani, Samuel R. Bowman, Kyunghyun Cho:
Can Unconditional Language Models Recover Arbitrary Sentences? CoRR abs/1907.04944 (2019) - [i112]Jungkyu Park, Jason Phang, Yiqiu Shen, Nan Wu, Sungheon Gene Kim, Linda Moy
Screening Mammogram Classification with Prior Exams. CoRR abs/1907.13057 (2019) - [i111]Thibault Févry, Jason Phang, Nan Wu, Sungheon Gene Kim, Linda Moy
Improving localization-based approaches for breast cancer screening exam classification. CoRR abs/1908.00615 (2019) - [i110]Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, Jason Weston:
Neural Text Generation with Unlikelihood Training. CoRR abs/1908.04319 (2019) - [i109]Raphael Shu, Jason Lee, Hideki Nakayama, Kyunghyun Cho:
Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference using a Delta Posterior. CoRR abs/1908.07181 (2019) - [i108]William F. Whitney, Rajat Agarwal, Kyunghyun Cho, Abhinav Gupta:
Dynamics-aware Embeddings. CoRR abs/1908.09357 (2019) - [i107]Katharina Kann, Kyunghyun Cho, Samuel R. Bowman:
Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set. CoRR abs/1909.01522 (2019) - [i106]Changhan Wang, Kyunghyun Cho, Jiatao Gu:
Neural Machine Translation with Byte-Level Subwords. CoRR abs/1909.03341 (2019) - [i105]Jason Lee, Kyunghyun Cho, Douwe Kiela:
Countering Language Drift via Visual Grounding. CoRR abs/1909.04499 (2019) - [i104]Ethan Perez, Siddharth Karamcheti, Rob Fergus, Jason Weston, Douwe Kiela, Kyunghyun Cho:
Finding Generalizable Evidence by Learning to Convince Q&A Models. CoRR abs/1909.05863 (2019) - [i103]Phu Mon Htut, Kyunghyun Cho, Samuel R. Bowman:
Inducing Constituency Trees through Neural Machine Translation. CoRR abs/1909.10056 (2019) - [i102]Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang:
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models. CoRR abs/1909.11299 (2019) - [i101]Edward Grefenstette, Brandon Amos, Denis Yarats, Phu Mon Htut, Artem Molchanov, Franziska Meier, Douwe Kiela, Kyunghyun Cho, Soumith Chintala:
Generalized Inner Loop Meta-Learning. CoRR abs/1910.01727 (2019) - [i100]Tianxing He, Jun Liu, Kyunghyun Cho, Myle Ott, Bing Liu, James R. Glass, Fuchun Peng:
Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models. CoRR abs/1910.07117 (2019) - [i99]Cinjon Resnick, Abhinav Gupta
Capacity, Bandwidth, and Compositionality in Emergent Language Learning. CoRR abs/1910.11424 (2019) - [i98]Rodrigo Frassetto Nogueira, Wei Yang, Kyunghyun Cho, Jimmy Lin:
Multi-Stage Document Ranking with BERT. CoRR abs/1910.14424 (2019) - [i97]Margaret Li, Stephen Roller, Ilia Kulikov, Sean Welleck, Y-Lan Boureau, Kyunghyun Cho, Jason Weston:
Don't Say That! Making Inconsistent Dialogue Unlikely with Unlikelihood Training. CoRR abs/1911.03860 (2019) - 2018
- [j15]Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio:
Fine-grained attention mechanism for neural machine translation. Neurocomputing 284: 171-176 (2018) - [j14]Çaglar Gülçehre
Dynamic Neural Turing Machine with Continuous and Discrete Addressing Schemes. Neural Comput. 30(4) (2018) - [j13]Sergey M. Plis, Md Faijul Amin, Adam Chekroud
Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia. NeuroImage 181: 734-747 (2018) - [j12]Keunwoo Choi
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging. IEEE Trans. Emerg. Top. Comput. Intell. 2(2): 139-149 (2018) - [c84]Jiatao Gu, Yong Wang, Kyunghyun Cho, Victor O. K. Li:
Search Engine Guided Neural Machine Translation. AAAI 2018: 5133-5140 - [c83]Lifu Huang, Heng Ji, Kyunghyun Cho, Ido Dagan, Sebastian Riedel, Clare R. Voss:
Zero-Shot Transfer Learning for Event Extraction. ACL (1) 2018: 2160-2170 - [c82]Changhan Wang, Kyunghyun Cho, Douwe Kiela:
Code-Switched Named Entity Recognition with Embedding Attention. CodeSwitch@ACL 2018: 154-158 - [c81]Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna:
Pommerman: A Multi-Agent Playground. AIIDE Workshops 2018 - [c80]Katharina Kann, Stanislas Lauly, Kyunghyun Cho:
The NYU System for the CoNLL-SIGMORPHON 2018 Shared Task on Universal Morphological Reinflection. CoNLL Shared Task (1) 2018: 58-63 - [c79]John E. Ortega, Weiyi Lu, Adam Meyers, Kyunghyun Cho:
Letting a Neural Network Decide Which Machine Translation System to Use for Black-Box Fuzzy-Match Repair. EAMT 2018: 229-238 - [c78]Jasmijn Bastings, Marco Baroni, Jason Weston, Kyunghyun Cho, Douwe Kiela:
Jump to better conclusions: SCAN both left and right. BlackboxNLP@EMNLP 2018: 47-55 - [c77]Lifu Huang, Kyunghyun Cho, Boliang Zhang, Heng Ji, Kevin Knight:
Multi-lingual Common Semantic Space Construction via Cluster-Consistent Word Embedding. EMNLP 2018: 250-260 - [c76]Phu Mon Htut, Kyunghyun Cho, Samuel R. Bowman:
Grammar Induction with Neural Language Models: An Unusual Replication. BlackboxNLP@EMNLP 2018: 371-373 - [c75]Yun Chen, Victor O. K. Li, Kyunghyun Cho, Samuel R. Bowman:
A Stable and Effective Learning Strategy for Trainable Greedy Decoding. EMNLP 2018: 380-390 - [c74]Jason Lee, Elman Mansimov, Kyunghyun Cho:
Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement. EMNLP 2018: 1173-1182 - [c73]Douwe Kiela, Changhan Wang, Kyunghyun Cho:
Dynamic Meta-Embeddings for Improved Sentence Representations. EMNLP 2018: 1466-1477 - [c72]Jiatao Gu, Yong Wang, Yun Chen, Victor O. K. Li, Kyunghyun Cho:
Meta-Learning for Low-Resource Neural Machine Translation. EMNLP 2018: 3622-3631 - [c71]Rujun Han, Michael Gill, Arthur Spirling, Kyunghyun Cho:
Conditional Word Embedding and Hypothesis Testing via Bayes-by-Backprop. EMNLP 2018: 4890-4895 - [c70]Phu Mon Htut, Kyunghyun Cho, Samuel R. Bowman:
Grammar Induction with Neural Language Models: An Unusual Replication. EMNLP 2018: 4998-5003 - [c69]Keunwoo Choi, György Fazekas, Mark B. Sandler
A Comparison of Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging. EUSIPCO 2018: 1870-1874 - [c68]Nan Wu, Krzysztof J. Geras, Yiqiu Shen
Breast Density Classification with Deep Convolutional Neural Networks. ICASSP 2018: 6682-6686 - [c67]Mikel Artetxe, Gorka Labaka, Eneko Agirre, Kyunghyun Cho:
Unsupervised Neural Machine Translation. ICLR (Poster) 2018 - [c66]Yun Chen, Kyunghyun Cho, Samuel R. Bowman, Victor O. K. Li:
Stable and Effective Trainable Greedy Decoding for Sequence to Sequence Learning. ICLR (Workshop) 2018 - [c65]Katrina Evtimova, Andrew Drozdov, Douwe Kiela, Kyunghyun Cho:
Emergent Communication in a Multi-Modal, Multi-Step Referential Game. ICLR (Poster) 2018 - [c64]R. Devon Hjelm, Athul Paul Jacob, Adam Trischler, Gerry Che, Kyunghyun Cho, Yoshua Bengio:
Boundary Seeking GANs. ICLR (Poster) 2018 - [c63]Jason Lee, Kyunghyun Cho, Jason Weston, Douwe Kiela:
Emergent Translation in Multi-Agent Communication. ICLR (Poster) 2018 - [c62]Phu Mon Htut, Samuel R. Bowman, Kyunghyun Cho:
Training a Ranking Function for Open-Domain Question Answering. NAACL-HLT (Student Research Workshop) 2018: 120-127 - [c61]Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho:
Loss Functions for Multiset Prediction. NeurIPS 2018: 5788-5797 - [c60]Rodrigo Frassetto Nogueira, Kyunghyun Cho:
New York University at TREC 2018 Complex Answer Retrieval Track. TREC 2018 - [i96]Jason Lee, Elman Mansimov, Kyunghyun Cho:
Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement. CoRR abs/1802.06901 (2018) - [i95]Jake Zhao, Kyunghyun Cho:
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples. CoRR abs/1802.09502 (2018) - [i94]Noah Weber, Leena Shekhar, Niranjan Balasubramanian, Kyunghyun Cho:
Controlling Decoding for More Abstractive Summaries with Copy-Based Networks. CoRR abs/1803.07038 (2018) - [i93]Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio:
Fine-Grained Attention Mechanism for Neural Machine Translation. CoRR abs/1803.11407 (2018) - [i92]Phu Mon Htut, Samuel R. Bowman, Kyunghyun Cho:
Training a Ranking Function for Open-Domain Question Answering. CoRR abs/1804.04264 (2018) - [i91]Cinjon Resnick, Ilya Kulikov, Kyunghyun Cho, Jason Weston:
Vehicle Community Strategies. CoRR abs/1804.07178 (2018) - [i90]Lifu Huang, Kyunghyun Cho, Boliang Zhang, Heng Ji, Kevin Knight:
Multi-lingual Common Semantic Space Construction via Cluster-consistent Word Embedding. CoRR abs/1804.07875 (2018) - [i89]Yun Chen, Victor O. K. Li, Kyunghyun Cho, Samuel R. Bowman:
A Stable and Effective Learning Strategy for Trainable Greedy Decoding. CoRR abs/1804.07915 (2018) - [i88]Douwe Kiela, Changhan Wang, Kyunghyun Cho:
Context-Attentive Embeddings for Improved Sentence Representations. CoRR abs/1804.07983 (2018) - [i87]Seokho Kang, Kyunghyun Cho:
Conditional molecular design with deep generative models. CoRR abs/1805.00108 (2018) - [i86]Konrad Zolna, Krzysztof J. Geras, Kyunghyun Cho:
Classifier-agnostic saliency map extraction. CoRR abs/1805.08249 (2018) - [i85]Xiaodong Gu, Kyunghyun Cho, Jung-Woo Ha, Sunghun Kim:
DialogWAE: Multimodal Response Generation with Conditional Wasserstein Auto-Encoder. CoRR abs/1805.12352 (2018) - [i84]Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville:
Learning Distributed Representations from Reviews for Collaborative Filtering. CoRR abs/1806.06875 (2018) - [i83]Cinjon Resnick, Roberta Raileanu, Sanyam Kapoor, Alex Peysakhovich, Kyunghyun Cho, Joan Bruna:
Backplay: "Man muss immer umkehren". CoRR abs/1807.06919 (2018) - [i82]Jiatao Gu, Yong Wang, Yun Chen, Kyunghyun Cho, Victor O. K. Li:
Meta-Learning for Low-Resource Neural Machine Translation. CoRR abs/1808.08437 (2018) - [i81]Phu Mon Htut, Kyunghyun Cho, Samuel R. Bowman:
Grammar Induction with Neural Language Models: An Unusual Replication. CoRR abs/1808.10000 (2018) - [i80]Jasmijn Bastings, Marco Baroni, Jason Weston, Kyunghyun Cho, Douwe Kiela:
Jump to better conclusions: SCAN both left and right. CoRR abs/1809.04640 (2018) - [i79]Cinjon Resnick, Wes Eldridge, David Ha, Denny Britz, Jakob N. Foerster, Julian Togelius, Kyunghyun Cho, Joan Bruna:
Pommerman: A Multi-Agent Playground. CoRR abs/1809.07124 (2018) - [i78]Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang:
Directional Analysis of Stochastic Gradient Descent via von Mises-Fisher Distributions in Deep learning. CoRR abs/1810.00150 (2018) - [i77]Sean Welleck, Jason Weston, Arthur Szlam, Kyunghyun Cho:
Dialogue Natural Language Inference. CoRR abs/1811.00671 (2018) - [i76]Ilya Kulikov, Alexander H. Miller, Kyunghyun Cho, Jason Weston:
Importance of a Search Strategy in Neural Dialogue Modelling. CoRR abs/1811.00907 (2018) - 2017
- [j11]Çaglar Gülçehre
On integrating a language model into neural machine translation. Comput. Speech Lang. 45: 137-148 (2017) - [j10]Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio:
Context-dependent word representation for neural machine translation. Comput. Speech Lang. 45: 149-160 (2017) - [j9]Orhan Firat, Kyunghyun Cho, Baskaran Sankaran, Fatos T. Yarman-Vural, Yoshua Bengio:
Multi-way, multilingual neural machine translation. Comput. Speech Lang. 45: 236-252 (2017) - [j8]Marta R. Costa-jussà, Alexandre Allauzen, Loïc Barrault
Introduction to the special issue on deep learning approaches for machine translation. Comput. Speech Lang. 46: 367-373 (2017) - [j7]Felix Hill
The representational geometry of word meanings acquired by neural machine translation models. Mach. Transl. 31(1-2): 3-18 (2017) - [j6]Jason Lee, Kyunghyun Cho, Thomas Hofmann:
Fully Character-Level Neural Machine Translation without Explicit Segmentation. Trans. Assoc. Comput. Linguistics 5: 365-378 (2017) - [c59]Jiakai Zhang, Kyunghyun Cho:
Query-Efficient Imitation Learning for End-to-End Simulated Driving. AAAI 2017: 2891-2897 - [c58]Akiko Eriguchi, Yoshimasa Tsuruoka
Learning to Parse and Translate Improves Neural Machine Translation. ACL (2) 2017: 72-78 - [c57]Sébastien Jean, Stanislas Lauly, Orhan Firat, Kyunghyun Cho:
Neural Machine Translation for Cross-Lingual Pronoun Prediction. DiscoMT@EMNLP 2017: 54-57 - [c56]Rico Sennrich, Orhan Firat, Kyunghyun Cho, Alexandra Birch, Barry Haddow, Julian Hitschler, Marcin Junczys-Dowmunt, Samuel Läubli, Antonio Valerio Miceli Barone
Nematus: a Toolkit for Neural Machine Translation. EACL (Software Demonstrations) 2017: 65-68 - [c55]Jiatao Gu, Graham Neubig, Kyunghyun Cho, Victor O. K. Li:
Learning to Translate in Real-time with Neural Machine Translation. EACL (1) 2017: 1053-1062 - [c54]Rodrigo Frassetto Nogueira, Kyunghyun Cho:
Task-Oriented Query Reformulation with Reinforcement Learning. EMNLP 2017: 574-583 - [c53]Jiatao Gu, Kyunghyun Cho, Victor O. K. Li:
Trainable Greedy Decoding for Neural Machine Translation. EMNLP 2017: 1968-1978 - [c52]Keunwoo Choi, György Fazekas, Mark B. Sandler
Convolutional recurrent neural networks for music classification. ICASSP 2017: 2392-2396 - [c51]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer Learning for Music Classification and Regression Tasks. ISMIR 2017: 141-149 - [c50]Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang:
Saliency-based Sequential Image Attention with Multiset Prediction. NIPS 2017: 5173-5183 - [e2]Phil Blunsom, Antoine Bordes, Kyunghyun Cho, Shay B. Cohen, Chris Dyer, Edward Grefenstette, Karl Moritz Hermann, Laura Rimell, Jason Weston, Scott Yih:
Proceedings of the 2nd Workshop on Representation Learning for NLP, Rep4NLP@ACL 2017, Vancouver, Canada, August 3, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-62-3 [contents] - [i75]Jiatao Gu, Kyunghyun Cho, Victor O. K. Li:
Trainable Greedy Decoding for Neural Machine Translation. CoRR abs/1702.02429 (2017) - [i74]Akiko Eriguchi, Yoshimasa Tsuruoka, Kyunghyun Cho:
Learning to Parse and Translate Improves Neural Machine Translation. CoRR abs/1702.03525 (2017) - [i73]R. Devon Hjelm, Athul Paul Jacob, Tong Che, Kyunghyun Cho, Yoshua Bengio:
Boundary-Seeking Generative Adversarial Networks. CoRR abs/1702.08431 (2017) - [i72]Rico Sennrich, Orhan Firat, Kyunghyun Cho, Alexandra Birch, Barry Haddow, Julian Hitschler, Marcin Junczys-Dowmunt, Samuel Läubli, Antonio Valerio Miceli Barone, Jozef Mokry, Maria Nadejde:
Nematus: a Toolkit for Neural Machine Translation. CoRR abs/1703.04357 (2017) - [i71]Krzysztof J. Geras, Stacey Wolfson, Sungheon Gene Kim, Linda Moy
High-Resolution Breast Cancer Screening with Multi-View Deep Convolutional Neural Networks. CoRR abs/1703.07047 (2017) - [i70]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer learning for music classification and regression tasks. CoRR abs/1703.09179 (2017) - [i69]Rodrigo Frassetto Nogueira, Kyunghyun Cho:
Task-Oriented Query Reformulation with Reinforcement Learning. CoRR abs/1704.04572 (2017) - [i68]Sébastien Jean, Stanislas Lauly, Orhan Firat, Kyunghyun Cho:
Does Neural Machine Translation Benefit from Larger Context? CoRR abs/1704.05135 (2017) - [i67]Matthew Dunn, Levent Sagun, Mike Higgins, V. Ugur Güney, Volkan Cirik, Kyunghyun Cho:
SearchQA: A New Q&A Dataset Augmented with Context from a Search Engine. CoRR abs/1704.05179 (2017) - [i66]Cem M. Deniz, Spencer Hallyburton, Arakua Welbeck, Stephen Honig, Kyunghyun Cho, Gregory Chang:
Segmentation of the Proximal Femur from MR Images using Deep Convolutional Neural Networks. CoRR abs/1704.06176 (2017) - [i65]Jiatao Gu, Yong Wang, Kyunghyun Cho, Victor O. K. Li:
Search Engine Guided Non-Parametric Neural Machine Translation. CoRR abs/1705.07267 (2017) - [i64]Katrina Evtimova
Emergent Language in a Multi-Modal, Multi-Step Referential Game. CoRR abs/1705.10369 (2017) - [i63]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
On the Robustness of Deep Convolutional Neural Networks for Music Classification. CoRR abs/1706.02361 (2017) - [i62]Lifu Huang, Heng Ji, Kyunghyun Cho, Clare R. Voss:
Zero-Shot Transfer Learning for Event Extraction. CoRR abs/1707.01066 (2017) - [i61]Kyunghyun Cho:
Strawman: an Ensemble of Deep Bag-of-Ngrams for Sentiment Analysis. CoRR abs/1707.08939 (2017) - [i60]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Comparison on Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging. CoRR abs/1709.01922 (2017) - [i59]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Tutorial on Deep Learning for Music Information Retrieval. CoRR abs/1709.04396 (2017) - [i58]Tian Wang, Kyunghyun Cho:
Attention-based Mixture Density Recurrent Networks for History-based Recommendation. CoRR abs/1709.07545 (2017) - [i57]Meihao Chen, Zhuoru Lin, Kyunghyun Cho:
Graph Convolutional Networks for Classification with a Structured Label Space. CoRR abs/1710.04908 (2017) - [i56]Jason Lee, Kyunghyun Cho, Jason Weston, Douwe Kiela:
Emergent Translation in Multi-Agent Communication. CoRR abs/1710.06922 (2017) - [i55]Mikel Artetxe, Gorka Labaka, Eneko Agirre, Kyunghyun Cho:
Unsupervised Neural Machine Translation. CoRR abs/1710.11041 (2017) - [i54]Nan Wu, Krzysztof J. Geras, Yiqiu Shen, Jingyi Su, Sungheon Gene Kim, Eric Kim, Stacey Wolfson, Linda Moy
Breast density classification with deep convolutional neural networks. CoRR abs/1711.03674 (2017) - [i53]Sean Welleck, Jialin Mao, Kyunghyun Cho, Zheng Zhang:
Saliency-based Sequential Image Attention with Multiset Prediction. CoRR abs/1711.05165 (2017) - [i52]Sean Welleck, Zixin Yao, Yu Gai, Jialin Mao, Zheng Zhang, Kyunghyun Cho:
Loss Functions for Multiset Prediction. CoRR abs/1711.05246 (2017) - [i51]Phil Blunsom, Kyunghyun Cho, Chris Dyer, Hinrich Schütze:
From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042). Dagstuhl Reports 7(1): 129-157 (2017) - 2016
- [j5]Felix Hill, KyungHyun Cho, Anna Korhonen, Yoshua Bengio:
Learning to Understand Phrases by Embedding the Dictionary. Trans. Assoc. Comput. Linguistics 4: 17-30 (2016) - [c49]Junyoung Chung, Kyunghyun Cho, Yoshua Bengio:
A Character-level Decoder without Explicit Segmentation for Neural Machine Translation. ACL (1) 2016 - [c48]Tian Wang, Kyunghyun Cho:
Larger-Context Language Modelling with Recurrent Neural Network. ACL (1) 2016 - [c47]Li Yao, Nicolas Ballas, Kyunghyun Cho, John R. Smith, Yoshua Bengio:
Oracle Performance for Visual Captioning. BMVC 2016 - [c46]Amrita Saha, Mitesh M. Khapra, Sarath Chandar, Janarthanan Rajendran, Kyunghyun Cho:
A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation. COLING 2016: 109-118 - [c45]Francesco Visin, Adriana Romero, Kyunghyun Cho, Matteo Matteucci, Marco Ciccone, Kyle Kastner, Yoshua Bengio, Aaron C. Courville:
ReSeg: A Recurrent Neural Network-Based Model for Semantic Segmentation. CVPR Workshops 2016: 426-433 - [c44]Orhan Firat, Baskaran Sankaran, Yaser Al-Onaizan, Fatos T. Yarman-Vural, Kyunghyun Cho:
Zero-Resource Translation with Multi-Lingual Neural Machine Translation. EMNLP 2016: 268-277 - [c43]Yasumasa Miyamoto, Kyunghyun Cho:
Gated Word-Character Recurrent Language Model. EMNLP 2016: 1992-1997 - [c42]Thien Huu Nguyen, Kyunghyun Cho, Ralph Grishman:
Joint Event Extraction via Recurrent Neural Networks. HLT-NAACL 2016: 300-309 - [c41]Orhan Firat, Kyunghyun Cho, Yoshua Bengio:
Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism. HLT-NAACL 2016: 866-875 - [c40]Felix Hill, Kyunghyun Cho, Anna Korhonen:
Learning Distributed Representations of Sentences from Unlabelled Data. HLT-NAACL 2016: 1367-1377 - [c39]Rodrigo Frassetto Nogueira, Kyunghyun Cho:
End-to-End Goal-Driven Web Navigation. NIPS 2016: 1903-1911 - [c38]R. Devon Hjelm, Russ Salakhutdinov, Kyunghyun Cho, Nebojsa Jojic, Vince D. Calhoun, Junyoung Chung:
Iterative Refinement of the Approximate Posterior for Directed Belief Networks. NIPS 2016: 4691-4699 - [c37]Thien Huu Nguyen, Lisheng Fu, Kyunghyun Cho, Ralph Grishman:
A Two-stage Approach for Extending Event Detection to New Types via Neural Networks. Rep4NLP@ACL 2016: 158-165 - [c36]Md Faijul Amin, Sergey M. Plis, Eswar Damaraju, R. Devon Hjelm, Kyunghyun Cho, Vince D. Calhoun
Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach. SSIAI 2016: 1-4 - [c35]Junyoung Chung, Kyunghyun Cho, Yoshua Bengio:
NYU-MILA Neural Machine Translation Systems for WMT'16. WMT 2016: 268-271 - [e1]Phil Blunsom, Kyunghyun Cho, Shay B. Cohen, Edward Grefenstette, Karl Moritz Hermann, Laura Rimell, Jason Weston, Scott Wen-tau Yih:
Proceedings of the 1st Workshop on Representation Learning for NLP, Rep4NLP@ACL 2016, Berlin, Germany, August 11, 2016. Association for Computational Linguistics 2016, ISBN 978-1-945626-04-3 [contents] - [i50]Orhan Firat, KyungHyun Cho, Yoshua Bengio:
Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism. CoRR abs/1601.01073 (2016) - [i49]Yijun Xiao, Kyunghyun Cho:
Efficient Character-level Document Classification by Combining Convolution and Recurrent Layers. CoRR abs/1602.00367 (2016) - [i48]Rodrigo Frassetto Nogueira, Kyunghyun Cho:
WebNav: A New Large-Scale Task for Natural Language based Sequential Decision Making. CoRR abs/1602.02261 (2016) - [i47]Felix Hill, Kyunghyun Cho, Anna Korhonen:
Learning Distributed Representations of Sentences from Unlabelled Data. CoRR abs/1602.03483 (2016) - [i46]Junyoung Chung, Kyunghyun Cho, Yoshua Bengio:
A Character-level Decoder without Explicit Segmentation for Neural Machine Translation. CoRR abs/1603.06147 (2016) - [i45]Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang:
Theano: A Python framework for fast computation of mathematical expressions. CoRR abs/1605.02688 (2016) - [i44]Kyunghyun Cho:
Noisy Parallel Approximate Decoding for Conditional Recurrent Language Model. CoRR abs/1605.03835 (2016) - [i43]Jiakai Zhang, Kyunghyun Cho:
Query-Efficient Imitation Learning for End-to-End Autonomous Driving. CoRR abs/1605.06450 (2016) - [i42]Yasumasa Miyamoto, Kyunghyun Cho:
Gated Word-Character Recurrent Language Model. CoRR abs/1606.01700 (2016) - [i41]Zhengping Che, Sanjay Purushotham, Kyunghyun Cho, David A. Sontag, Yan Liu:
Recurrent Neural Networks for Multivariate Time Series with Missing Values. CoRR abs/1606.01865 (2016) - [i40]Kyunghyun Cho, Masha Esipova:
Can neural machine translation do simultaneous translation? CoRR abs/1606.02012 (2016) - [i39]Amjad Almahairi, Kyunghyun Cho, Nizar Habash, Aaron C. Courville:
First Result on Arabic Neural Machine Translation. CoRR abs/1606.02680 (2016) - [i38]Orhan Firat, Baskaran Sankaran, Yaser Al-Onaizan, Fatos T. Yarman-Vural, Kyunghyun Cho:
Zero-Resource Translation with Multi-Lingual Neural Machine Translation. CoRR abs/1606.04164 (2016) - [i37]Amrita Saha, Mitesh M. Khapra, Sarath Chandar, Janarthanan Rajendran, Kyunghyun Cho:
A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation. CoRR abs/1606.04754 (2016) - [i36]Çaglar Gülçehre, Sarath Chandar, Kyunghyun Cho, Yoshua Bengio:
Dynamic Neural Turing Machine with Soft and Hard Addressing Schemes. CoRR abs/1607.00036 (2016) - [i35]Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio:
Context-Dependent Word Representation for Neural Machine Translation. CoRR abs/1607.00578 (2016) - [i34]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional Recurrent Neural Networks for Music Classification. CoRR abs/1609.04243 (2016) - [i33]Jiatao Gu, Graham Neubig, Kyunghyun Cho, Victor O. K. Li:
Learning to Translate in Real-time with Neural Machine Translation. CoRR abs/1610.00388 (2016) - [i32]Jason Lee, Kyunghyun Cho, Thomas Hofmann:
Fully Character-Level Neural Machine Translation without Explicit Segmentation. CoRR abs/1610.03017 (2016) - [i31]Hyo-Eun Kim, Sangheum Hwang, Kyunghyun Cho:
Semantic Noise Modeling for Better Representation Learning. CoRR abs/1611.01268 (2016) - 2015
- [j4]Hannes Schulz, KyungHyun Cho, Tapani Raiko
Two-layer contractive encodings for learning stable nonlinear features. Neural Networks 64: 4-11 (2015) - [j3]Mathias Berglund, Tapani Raiko
Measuring the usefulness of hidden units in Boltzmann machines with mutual information. Neural Networks 64: 12-18 (2015) - [j2]Kyunghyun Cho, Aaron C. Courville, Yoshua Bengio:
Describing Multimedia Content Using Attention-Based Encoder-Decoder Networks. IEEE Trans. Multim. 17(11): 1875-1886 (2015) - [c34]Sébastien Jean, KyungHyun Cho, Roland Memisevic, Yoshua Bengio:
On Using Very Large Target Vocabulary for Neural Machine Translation. ACL (1) 2015: 1-10 - [c33]Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher J. Pal, Hugo Larochelle, Aaron C. Courville:
Describing Videos by Exploiting Temporal Structure. ICCV 2015: 4507-4515 - [c32]Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio:
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. ICML 2015: 2048-2057 - [c31]Junyoung Chung, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio:
Gated Feedback Recurrent Neural Networks. ICML 2015: 2067-2075 - [c30]Liang Lu, Xingxing Zhang, Kyunghyun Cho, Steve Renals:
A study of the recurrent neural network encoder-decoder for large vocabulary speech recognition. INTERSPEECH 2015: 3249-3253 - [c29]Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, Kyunghyun Cho, Yoshua Bengio:
Attention-Based Models for Speech Recognition. NIPS 2015: 577-585 - [c28]Amjad Almahairi, Kyle Kastner, Kyunghyun Cho, Aaron C. Courville:
Learning Distributed Representations from Reviews for Collaborative Filtering. RecSys 2015: 147-154 - [c27]Sébastien Jean, Orhan Firat, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio:
Montreal Neural Machine Translation Systems for WMT'15. WMT@EMNLP 2015: 134-140 - [c26]Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio:
Neural Machine Translation by Jointly Learning to Align and Translate. ICLR 2015 - [c25]Felix Hill, Kyunghyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio:
Embedding Word Similarity with Neural Machine Translation. ICLR (Workshop) 2015 - [i30]Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio:
Gated Feedback Recurrent Neural Networks. CoRR abs/1502.02367 (2015) - [i29]Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron C. Courville, Ruslan Salakhutdinov, Richard S. Zemel, Yoshua Bengio:
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention. CoRR abs/1502.03044 (2015) - [i28]Li Yao, Atousa Torabi, Kyunghyun Cho, Nicolas Ballas, Christopher Joseph Pal, Hugo Larochelle, Aaron C. Courville:
Video Description Generation Incorporating Spatio-Temporal Features and a Soft-Attention Mechanism. CoRR abs/1502.08029 (2015) - [i27]Çaglar Gülçehre, Orhan Firat, Kelvin Xu, Kyunghyun Cho, Loïc Barrault, Huei-Chi Lin, Fethi Bougares, Holger Schwenk, Yoshua Bengio:
On Using Monolingual Corpora in Neural Machine Translation. CoRR abs/1503.03535 (2015) - [i26]Felix Hill, Kyunghyun Cho, Anna Korhonen, Yoshua Bengio:
Learning to Understand Phrases by Embedding the Dictionary. CoRR abs/1504.00548 (2015) - [i25]Francesco Visin, Kyle Kastner, Kyunghyun Cho, Matteo Matteucci, Aaron C. Courville, Yoshua Bengio:
ReNet: A Recurrent Neural Network Based Alternative to Convolutional Networks. CoRR abs/1505.00393 (2015) - [i24]Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, KyungHyun Cho, Yoshua Bengio:
Attention-Based Models for Speech Recognition. CoRR abs/1506.07503 (2015) - [i23]KyungHyun Cho, Aaron C. Courville, Yoshua Bengio:
Describing Multimedia Content using Attention-based Encoder-Decoder Networks. CoRR abs/1507.01053 (2015) - [i22]Tian Wang, Kyunghyun Cho:
Larger-Context Language Modelling. CoRR abs/1511.03729 (2015) - [i21]Li Yao, Nicolas Ballas, KyungHyun Cho, John R. Smith, Yoshua Bengio:
Trainable performance upper bounds for image and video captioning. CoRR abs/1511.04590 (2015) - [i20]R. Devon Hjelm, Kyunghyun Cho, Junyoung Chung, Ruslan Salakhutdinov, Vince D. Calhoun, Nebojsa Jojic:
Iterative Refinement of Approximate Posterior for Training Directed Belief Networks. CoRR abs/1511.06382 (2015) - [i19]Quan Gan, Qipeng Guo, Zheng Zhang, Kyunghyun Cho:
First Step toward Model-Free, Anonymous Object Tracking with Recurrent Neural Networks. CoRR abs/1511.06425 (2015) - [i18]Marcin Moczulski, Kelvin Xu, Aaron C. Courville, KyungHyun Cho:
A Controller Recognizer Framework: How necessary is recognition for control? CoRR abs/1511.06428 (2015) - [i17]Francesco Visin, Kyle Kastner, Aaron C. Courville, Yoshua Bengio, Matteo Matteucci, KyungHyun Cho:
ReSeg: A Recurrent Neural Network for Object Segmentation. CoRR abs/1511.07053 (2015) - [i16]Kyunghyun Cho:
Natural Language Understanding with Distributed Representation. CoRR abs/1511.07916 (2015) - 2014
- [b1]Kyunghyun Cho:
Foundations and Advances in Deep Learning. Aalto University, Helsinki, Finland, 2014 - [c24]Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. EMNLP 2014: 1724-1734 - [c23]Tapani Raiko, Li Yao, KyungHyun Cho, Yoshua Bengio:
Iterative Neural Autoregressive Distribution Estimator NADE-k. NIPS 2014: 325-333 - [c22]Guido Montúfar, Razvan Pascanu, KyungHyun Cho, Yoshua Bengio:
On the Number of Linear Regions of Deep Neural Networks. NIPS 2014: 2924-2932 - [c21]Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, KyungHyun Cho, Surya Ganguli, Yoshua Bengio:
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. NIPS 2014: 2933-2941 - [c20]Li Yao, Sherjil Ozair, KyungHyun Cho, Yoshua Bengio:
On the Equivalence between Deep NADE and Generative Stochastic Networks. ECML/PKDD (3) 2014: 322-336 - [c19]Çaglar Gülçehre
Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks. ECML/PKDD (1) 2014: 530-546 - [c18]Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer, Kyunghyun Cho, Yoshua Bengio:
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation. SSST@EMNLP 2014: 78-85 - [c17]Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, Yoshua Bengio:
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches. SSST@EMNLP 2014: 103-111 - [c16]Kyunghyun Cho, Xi Chen:
Classifying and Visualizing Motion Capture Sequences using Deep Neural Networks. VISAPP (2) 2014: 122-130 - [c15]Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio:
How to Construct Deep Recurrent Neural Networks. ICLR (Poster) 2014 - [i15]Guido Montúfar, Razvan Pascanu, Kyunghyun Cho, Yoshua Bengio:
On the Number of Linear Regions of Deep Neural Networks. CoRR abs/1402.1869 (2014) - [i14]Kyunghyun Cho, Bart van Merrienboer, Çaglar Gülçehre, Fethi Bougares, Holger Schwenk, Yoshua Bengio:
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. CoRR abs/1406.1078 (2014) - [i13]Tapani Raiko, Li Yao, Kyunghyun Cho, Yoshua Bengio:
Iterative Neural Autoregressive Distribution Estimator (NADE-k). CoRR abs/1406.1485 (2014) - [i12]Yann N. Dauphin, Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio:
Identifying and attacking the saddle point problem in high-dimensional non-convex optimization. CoRR abs/1406.2572 (2014) - [i11]Kyunghyun Cho, Yoshua Bengio:
Exponentially Increasing the Capacity-to-Computation Ratio for Conditional Computation in Deep Learning. CoRR abs/1406.7362 (2014) - [i10]Li Yao, Sherjil Ozair, Kyunghyun Cho, Yoshua Bengio:
On the Equivalence Between Deep NADE and Generative Stochastic Networks. CoRR abs/1409.0585 (2014) - [i9]Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer, KyungHyun Cho, Yoshua Bengio:
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation. CoRR abs/1409.1257 (2014) - [i8]KyungHyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, Yoshua Bengio:
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches. CoRR abs/1409.1259 (2014) - [i7]Felix Hill, KyungHyun Cho, Sébastien Jean, Coline Devin, Yoshua Bengio:
Not All Neural Embeddings are Born Equal. CoRR abs/1410.0718 (2014) - [i6]Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio:
End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results. CoRR abs/1412.1602 (2014) - [i5]Sébastien Jean, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio:
On Using Very Large Target Vocabulary for Neural Machine Translation. CoRR abs/1412.2007 (2014) - [i4]Junyoung Chung, Çaglar Gülçehre, KyungHyun Cho, Yoshua Bengio:
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling. CoRR abs/1412.3555 (2014) - 2013
- [j1]KyungHyun Cho, Tapani Raiko, Alexander Ilin:
Enhanced Gradient for Training Restricted Boltzmann Machines. Neural Comput. 25(3): 805-831 (2013) - [c14]KyungHyun Cho, Tapani Raiko, Alexander Ilin, Juha Karhunen:
A Two-Stage Pretraining Algorithm for Deep Boltzmann Machines. ICANN 2013: 106-113 - [c13]KyungHyun Cho:
Boltzmann Machines for Image Denoising. ICANN 2013: 611-618 - [c12]Sami Keronen, KyungHyun Cho, Tapani Raiko, Alexander Ilin, Kalle J. Palomäki:
Gaussian-Bernoulli restricted Boltzmann machines and automatic feature extraction for noise robust missing data mask estimation. ICASSP 2013: 6729-6733 - [c11]Kyunghyun Cho:
Simple Sparsification Improves Sparse Denoising Autoencoders in Denoising Highly Corrupted Images. ICML (3) 2013: 432-440 - [c10]Hannes Schulz, KyungHyun Cho, Tapani Raiko, Sven Behnke
Two-Layer Contractive Encodings with Shortcuts for Semi-supervised Learning. ICONIP (1) 2013: 450-457 - [c9]KyungHyun Cho:
Understanding Dropout: Training Multi-Layer Perceptrons with Auxiliary Independent Stochastic Neurons. ICONIP (1) 2013: 474-481 - [c8]Mathias Berglund, Tapani Raiko, KyungHyun Cho:
Measuring the Usefulness of Hidden Units in Boltzmann Machines with Mutual Information. ICONIP (1) 2013: 482-489 - [c7]KyungHyun Cho, Tapani Raiko, Alexander Ilin:
Gaussian-Bernoulli deep Boltzmann machine. IJCNN 2013: 1-7 - [c6]Kyunghyun Cho:
Boltzmann Machines and Denoising Autoencoders for Image Denoising. ICLR (Workshop Poster) 2013 - [i3]Kyunghyun Cho:
Understanding Dropout: Training Multi-Layer Perceptrons with Auxiliary Independent Stochastic Neurons. CoRR abs/1306.2801 (2013) - [i2]Kyunghyun Cho, Xi Chen:
Classifying and Visualizing Motion Capture Sequences using Deep Neural Networks. CoRR abs/1306.3874 (2013) - [i1]Çaglar Gülçehre, Kyunghyun Cho, Razvan Pascanu, Yoshua Bengio:
Learned-norm pooling for deep neural networks. CoRR abs/1311.1780 (2013) - 2012
- [c5]KyungHyun Cho, Alexander Ilin, Tapani Raiko:
Tikhonov-Type Regularization for Restricted Boltzmann Machines. ICANN (1) 2012: 81-88 - [c4]KyungHyun Cho, Nima Reyhani:
An iterative algorithm for singular value decomposition on noisy incomplete matrices. IJCNN 2012: 1-6 - 2011
- [c3]KyungHyun Cho, Alexander Ilin, Tapani Raiko:
Improved Learning of Gaussian-Bernoulli Restricted Boltzmann Machines. ICANN (1) 2011: 10-17 - [c2]KyungHyun Cho, Tapani Raiko, Alexander Ilin:
Enhanced Gradient and Adaptive Learning Rate for Training Restricted Boltzmann Machines. ICML 2011: 105-112 - 2010
- [c1]KyungHyun Cho, Tapani Raiko, Alexander Ilin:
Parallel tempering is efficient for learning restricted Boltzmann machines. IJCNN 2010: 1-8
Coauthor Index
[j15] [j14] [c64] [i93] [j11] [j10] [j9] [j7] [i73] [j5] [c49] [c47] [c45] [c41] [c35] [i50] [i46] [i45] [i36] [i35] [j2] [c34] [c32] [c31] [c29] [c27] [c26] [c25] [i30] [i29] [i27] [i26] [i25] [i24] [i23] [i21] [i17] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [c17] [c15] [i15] [i14] [i13] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [i5] [i4] [i1]
Richard Bonneau
aka: Richard A. Bonneau
aka: Richard A. Bonneau
Caglar Gulcehre
aka: Çaglar Gülçehre
aka: Çaglar Gülçehre
Ilia Kulikov
aka: Ilya Kulikov
aka: Ilya Kulikov
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