Tao, Chenyang

20 publications

ECCV 2024 CroMo-Mixup: Augmenting Cross-Model Representations for Continual Self-Supervised Learning Erum Mushtaq, Duygu Nur Yaldiz, Yavuz Faruk Bakman, Jie Ding, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

ICML 2024 DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models Sidi Lu, Wenbo Zhao, Chenyang Tao, Arpit Gupta, Shanchan Wu, Tagyoung Chung, Nanyun Peng

ICLRW 2024 MARS: Meaning-Aware Response Scoring for Uncertainty Estimation in Generative LLMs Yavuz Faruk Bakman, Duygu Nur Yaldiz, Baturalp Buyukates, Chenyang Tao, Dimitrios Dimitriadis, Salman Avestimehr

NeurIPSW 2023 How Do Large Multimodal Models Really Fare in Classical Vision Few-Shot Challenges? a Deep Dive Qing Guo, Prashan Wanigasekara, Jian Zheng, Jacob Zhiyuan Fang, Xinwei Deng, Chenyang Tao

ICLR 2022 Gradient Importance Learning for Incomplete Observations Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic

NeurIPS 2022 Tight Mutual Information Estimation with Contrastive Fenchel-Legendre Optimization Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Jing Huang, Larry Carin, Fan Li, Chenyang Tao

NeurIPSW 2022 Weakly Supervised Data Augmentation Through Prompting for Dialogue Understanding Maximillian Chen, Alexandros Papangelis, Chenyang Tao, Andy Rosenbaum, Seokhwan Kim, Yang Liu, Zhou Yu, Dilek Hakkani-Tur

AISTATS 2021 Counterfactual Representation Learning with Balancing Weights Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin

NeurIPS 2021 Supercharging Imbalanced Data Learning with Energy-Based Contrastive Representation Transfer Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao

AAAI 2021 Variational Disentanglement for Rare Event Modeling Zidi Xiu, Chenyang Tao, Michael Gao, Connor Davis, Benjamin Alan Goldstein, Ricardo Henao

NeurIPS 2020 Reconsidering Generative Objectives for Counterfactual Reasoning Danni Lu, Chenyang Tao, Junya Chen, Fan Li, Feng Guo, Lawrence Carin

AAAI 2020 Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin

ICLR 2019 Improving Sequence-to-Sequence Learning via Optimal Transport Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin

NeurIPS 2019 Improving Textual Network Learning with Variational Homophilic Embeddings Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin

NeurIPS 2019 On Fenchel Mini-Max Learning Chenyang Tao, Liqun Chen, Shuyang Dai, Junya Chen, Ke Bai, Dong Wang, Jianfeng Feng, Wenlian Lu, Georgiy Bobashev, Lawrence Carin

ICML 2019 Variational Annealing of GANs: A Langevin Perspective Chenyang Tao, Shuyang Dai, Liqun Chen, Ke Bai, Junya Chen, Chang Liu, Ruiyi Zhang, Georgiy Bobashev, Lawrence Carin Duke

NeurIPS 2018 Adversarial Text Generation via Feature-Mover's Distance Liqun Chen, Shuyang Dai, Chenyang Tao, Haichao Zhang, Zhe Gan, Dinghan Shen, Yizhe Zhang, Guoyin Wang, Ruiyi Zhang, Lawrence Carin

ICML 2018 Adversarial Time-to-Event Modeling Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Goldstein, Lawrence Carin Duke, Ricardo Henao

ICML 2018 Chi-Square Generative Adversarial Network Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin Duke

ICML 2018 Variational Inference and Model Selection with Generalized Evidence Bounds Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin Duke