Leveraging Video Descriptions to Learn Video Question Answering. - Kuo-Hao Zeng; Tseng-Hung Chen; Ching-Yao Chuang; Yuan-Hong Liao; Juan Carlos Niebles; Min Sun 001 (AAAI, 2017)

Show, Adapt and Tell: Adversarial Training of Cross-Domain Image Captioner. - Tseng-Hung Chen; Yuan-Hong Liao; Ching-Yao Chuang; Wan Ting Hsu; Jianlong Fu; Min Sun (ICCV, 2017)

Learning to Act Properly: Predicting and Explaining Affordances From Images. - Ching-Yao Chuang; Jiaman Li; Antonio Torralba 001; Sanja Fidler (CVPR, 2018)

The Role of Embedding Complexity in Domain-invariant Representations. - Ching-Yao Chuang; Antonio Torralba 001; Stefanie Jegelka (CoRR, 2019)

Estimating Generalization under Distribution Shifts via Domain-Invariant Representations. - Ching-Yao Chuang; Antonio Torralba 001; Stefanie Jegelka (ICML, 2020)

Debiased Contrastive Learning. - Ching-Yao Chuang; Joshua Robinson 001; Yen-Chen Lin; Antonio Torralba 001; Stefanie Jegelka (NeurIPS, 2020)

Fair Mixup: Fairness via Interpolation. - Ching-Yao Chuang; Youssef Mroueh (ICLR, 2021)

Contrastive Learning with Hard Negative Samples. - Joshua David Robinson; Ching-Yao Chuang; Suvrit Sra; Stefanie Jegelka (ICLR, 2021)

Measuring Generalization with Optimal Transport. - Ching-Yao Chuang; Youssef Mroueh; Kristjan H. Greenewald; Antonio Torralba 001; Stefanie Jegelka (NeurIPS, 2021)

Robust Contrastive Learning against Noisy Views. - Ching-Yao Chuang; R. Devon Hjelm; Xin Wang 066; Vibhav Vineet; Neel Joshi; Antonio Torralba 001; Stefanie Jegelka; Yale Song (CVPR, 2022)

Tree Mover's Distance: Bridging Graph Metrics and Stability of Graph Neural Networks. - Ching-Yao Chuang; Stefanie Jegelka (NeurIPS, 2022)

InfoOT: Information Maximizing Optimal Transport. - Ching-Yao Chuang; Stefanie Jegelka; David Alvarez-Melis (ICML, 2023)

What is the Inductive Bias of Flatness Regularization? A Study of Deep Matrix Factorization Models. - Khashayar Gatmiry; Zhiyuan Li 005; Tengyu Ma 001; Sashank J. Reddi; Stefanie Jegelka; Ching-Yao Chuang (NeurIPS, 2023)

Debiasing Vision-Language Models via Biased Prompts. - Ching-Yao Chuang; Varun Jampani; Yuanzhen Li; Antonio Torralba 001; Stefanie Jegelka (CoRR, 2023)

The Inductive Bias of Flatness Regularization for Deep Matrix Factorization. - Khashayar Gatmiry; Zhiyuan Li 005; Ching-Yao Chuang; Sashank J. Reddi; Tengyu Ma 001; Stefanie Jegelka (CoRR, 2023)

Robust Learning from Uncurated Data - Ching-Yao Chuang (2023)

Fairy: Fast Parallelized Instruction-Guided Video-to-Video Synthesis. - Bichen Wu; Ching-Yao Chuang; Xiaoyan Wang; Yichen Jia; Kapil Krishnakumar; Tong Xiao; Feng Liang; Licheng Yu; Peter Vajda (CVPR, 2024)

Movie Gen: A Cast of Media Foundation Models. - Adam Polyak; Amit Zohar; Andrew Brown; Andros Tjandra; Animesh Sinha; Ann Lee 001; Apoorv Vyas; Bowen Shi; Chih-Yao Ma; Ching-Yao Chuang; David Yan; Dhruv Choudhary; et al. (CoRR, 2024)

Populate-A-Scene: Affordance-Aware Human Video Generation. - Mengyi Shan; Zecheng He; Haoyu Ma; Felix Juefei-Xu; Peizhao Zhang; Tingbo Hou; Ching-Yao Chuang (CoRR, 2025)