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ORCIDKyunghyun 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, 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, Michael Krone, Cláudio T. Silva:
: Visualization of AI-Assisted Task Guidance in AR. IEEE Trans. Vis. Comput. Graph. 30(1): 1313-1323 (2024) - [c180]Taeyeon Kim, Hyun-Song Kwon, Kyunghyun Cho, Woontack Woo:
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 - [i262]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) - [i261]Weizhe Yuan, Richard Yuanzhe Pang, Kyunghyun Cho, Sainbayar Sukhbaatar, Jing Xu, Jason Weston:
Self-Rewarding Language Models. CoRR abs/2401.10020 (2024) - [i260]Sungmin Cha, Kyunghyun Cho:
Hyperparameters in Continual Learning: a Reality Check. CoRR abs/2403.09066 (2024) - [i259]Saksham Bassi, Duygu Ataman, Kyunghyun Cho:
Generalization Measures for Zero-Shot Cross-Lingual Transfer. CoRR abs/2404.15928 (2024) - [i258]Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, He He, Sainbayar Sukhbaatar, Jason Weston:
Iterative Reasoning Preference Optimization. CoRR abs/2404.19733 (2024) - [i257]Chaojie Zhang, Shengjia Chen, Ozkan Cigdem, Haresh Rengaraj Rajamohan, Kyunghyun Cho, Richard Kijowski, Cem M. Deniz:
MR-Transformer: Vision Transformer for Total Knee Replacement Prediction Using Magnetic Resonance Imaging. CoRR abs/2405.02784 (2024) - [i256]Kyunghyun Cho:
A Brief Introduction to Causal Inference in Machine Learning. CoRR abs/2405.08793 (2024) - [i255]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) - [i254]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) - [i253]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) - [i252]Siavash Golkar, Alberto Bietti, Mariel Pettee, Michael Eickenberg, Miles D. Cranmer, Keiya Hirashima, Géraud Krawezik, Nicholas Lourie, Michael McCabe, Rudy Morel, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Kyunghyun Cho, Shirley Ho:
Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task. CoRR abs/2406.02585 (2024) - [i251]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) - [i250]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) - [i249]Weizhe Yuan, Ilia Kulikov, Ping Yu, Kyunghyun Cho, Sainbayar Sukhbaatar, Jason Weston, Jing Xu:
Following Length Constraints in Instructions. CoRR abs/2406.17744 (2024) - [i248]Samuel Stanton, Robert G. Alberstein, Nathan C. Frey, Andrew M. Watkins, Kyunghyun Cho:
Closed-Form Test Functions for Biophysical Sequence Optimization Algorithms. CoRR abs/2407.00236 (2024) - [i247]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) - [i246]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) - [i245]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) - [i244]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) - [i243]Yuanqing Wang, Kyunghyun Cho:
Non-convolutional Graph Neural Networks. CoRR abs/2408.00165 (2024) - [i242]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) - [i241]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) - [i240]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) - [i239]Daniel Jiwoong Im, Kevin Zhang, Nakul Verma, Kyunghyun Cho:
Using Deep Autoregressive Models as Causal Inference Engines. CoRR abs/2409.18581 (2024) - [i238]Andreas Loukas, Karolis Martinkus, Ed Wagstaff, Kyunghyun Cho:
Generalizing to any diverse distribution: uniformity, gentle finetuning and rebalancing. CoRR abs/2410.05980 (2024) - [i237]Angelica Chen, Samuel Don Stanton, Robert G. Alberstein, Andrew M. Watkins, Richard Bonneau, Vladimir Gligorijevic, Kyunghyun Cho, Nathan C. Frey:
LLMs are Highly-Constrained Biophysical Sequence Optimizers. CoRR abs/2410.22296 (2024) - 2023
- [j31]Lavender Yao Jiang, Xujin Chris Liu, Nima Pour Nejatian, Mustafa Nasir-Moin, Duo Wang, Anas Z. Abidin, Kevin Eaton, Howard Antony Riina, Ilya Laufer, Paawan Punjabi, Madeline Miceli, Nora C. Kim, Cordelia Orillac, Zane Schnurman, Christopher Livia, Hannah Weiss, David Kurland, Sean Neifert, Yosef Dastagirzada, Douglas Kondziolka, Alexander T. M. Cheung, Grace Yang, Ming Cao, Mona Flores, Anthony B. Costa, Yindalon Aphinyanaphongs, Kyunghyun Cho, Eric Karl Oermann:
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, Chenkang Zhang, Muru Wu, Xujin Liu, Lavender Y. Jiang, Kyunghyun Cho, Eric K. Oermann:
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, Jinyeong Bak, Kyunghyun Cho, Hyungjoon Koo:
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, Michael Krone, Cláudio T. Silva:
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, Géraud Krawezik, François Lanusse, Michael McCabe, Ruben Ohana, Liam Holden Parker, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho:
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, Alberto Bietti, Michael Eickenberg, Siavash Golkar, Géraud Krawezik, François Lanusse, Mariel Pettee, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho:
Multiple Physics Pretraining for Physical Surrogate Models. CoRR abs/2310.02994 (2023) - [i213]François Lanusse, Liam Holden Parker, Siavash Golkar, Miles D. Cranmer, Alberto Bietti, Michael Eickenberg, Géraud Krawezik, Michael McCabe, Ruben Ohana, Mariel Pettee, Bruno Régaldo-Saint Blancard, Tiberiu Tesileanu, Kyunghyun Cho, Shirley Ho:
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, Kyunghyun Cho, Richard Bonneau:
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, Michael Picheny, Kyunghyun Cho:
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, Nako Sung:
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, Kyunghyun Cho, Alice Oh:
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]