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2020 – today
- 2026
[i16]Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh:
LoL: Longer than Longer, Scaling Video Generation to Hour. CoRR abs/2601.16914 (2026)- [i15]Jingran Zhang, Ning Li, Yuanhao Ban, Andrew Bai, Justin Cui:
Reward-Forcing: Autoregressive Video Generation with Reward Feedback. CoRR abs/2601.16933 (2026) - 2025
- [c3]Andrew Bai, Chih-Kuan Yeh, Cho-Jui Hsieh, Ankur Taly:
An Efficient Rehearsal Scheme for Catastrophic Forgetting Mitigation during Multi-stage Fine-tuning. NAACL (Findings) 2025: 2557-2569 - [i14]Li-Cheng Lan, Andrew Bai, Minhao Cheng, Cho-Jui Hsieh, Tianyi Zhou
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Exploring Expert Failures Improves LLM Agent Tuning. CoRR abs/2504.13145 (2025) - [i13]Yunqi Hong, Sohyun An, Andrew Bai, Neil Y. C. Lin, Cho-Jui Hsieh:
Unlabeled Data Improves Fine-Grained Image Zero-shot Classification with Multimodal LLMs. CoRR abs/2506.03195 (2025) - [i12]Andrew Bai, Justin Cui, Ruochen Wang, Cho-Jui Hsieh:
Concepts or Skills? Rethinking Instruction Selection for Multi-modal Models. CoRR abs/2508.10339 (2025) - [i11]Justin Cui, Jie Wu, Ming Li, Tao Yang, Xiaojie Li, Rui Wang, Andrew Bai, Yuanhao Ban, Cho-Jui Hsieh:
Self-Forcing++: Towards Minute-Scale High-Quality Video Generation. CoRR abs/2510.02283 (2025) - [i10]Kai-Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho-Jui Hsieh, Neil Y. C. Lin:
Uncertainty-Guided Selective Adaptation Enables Cross-Platform Predictive Fluorescence Microscopy. CoRR abs/2511.12006 (2025) - [i9]Tong Xie, Andrew Bai, Yuanhao Ban, Yunqi Hong, Haoyu Li, Cho-Jui Hsieh:
When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models. CoRR abs/2512.06343 (2025) - 2024
- [j2]Tong Xie, Haoyu Li, Andrew Bai, Cho-Jui Hsieh:
Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation. Trans. Mach. Learn. Res. 2024 (2024) - [c2]Yihan Wang, Zhouxing Shi, Andrew Bai, Cho-Jui Hsieh:
Defending LLMs against Jailbreaking Attacks via Backtranslation. ACL (Findings) 2024: 16031-16046 - [i8]Tong Xie, Haoyu Li, Andrew Bai, Cho-Jui Hsieh:
Data Attribution for Diffusion Models: Timestep-induced Bias in Influence Estimation. CoRR abs/2401.09031 (2024) - [i7]Andrew Bai, Chih-Kuan Yeh, Cho-Jui Hsieh, Ankur Taly:
Which Pretrain Samples to Rehearse when Finetuning Pretrained Models? CoRR abs/2402.08096 (2024) - [i6]Yihan Wang, Zhouxing Shi, Andrew Bai, Cho-Jui Hsieh:
Defending LLMs against Jailbreaking Attacks via Backtranslation. CoRR abs/2402.16459 (2024) - [i5]Jack He, Jianxing Zhao, Andrew Bai, Cho-Jui Hsieh:
Embedding Space Selection for Detecting Memorization and Fingerprinting in Generative Models. CoRR abs/2407.21159 (2024) - [i4]Yu-Hsiang Wang, Andrew Bai, Che-Ping Tsai, Cho-Jui Hsieh:
CLUE: Concept-Level Uncertainty Estimation for Large Language Models. CoRR abs/2409.03021 (2024) - [i3]Yihan Wang, Andrew Bai, Nanyun Peng, Cho-Jui Hsieh:
On the loss of context-awareness in general instruction fine-tuning. CoRR abs/2411.02688 (2024) - 2023
- [c1]Andrew Bai, Chih-Kuan Yeh, Neil Y. C. Lin, Pradeep Kumar Ravikumar, Cho-Jui Hsieh:
Concept Gradient: Concept-based Interpretation Without Linear Assumption. ICLR 2023 - 2022
- [i2]Andrew Bai, Chih-Kuan Yeh, Pradeep Ravikumar, Neil Y. C. Lin, Cho-Jui Hsieh:
Concept Gradient: Concept-based Interpretation Without Linear Assumption. CoRR abs/2208.14966 (2022) - [i1]Andrew Bai, Cho-Jui Hsieh, Wendy Chi-wen Kan, Hsuan-Tien Lin:
Reducing Training Sample Memorization in GANs by Training with Memorization Rejection. CoRR abs/2210.12231 (2022) - 2021
- [j1]Xinhe Chen, Kai Wu, Andrew Bai, Cornelius M. Masuku, Jacques Niederberger, Fábio S. Liporace, Lorenz T. Biegler:
Real-time refinery optimization with reduced-order fluidized catalytic cracker model and surrogate-based trust region filter method. Comput. Chem. Eng. 153: 107455 (2021)
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