Publications

^* indicates equal contribution.

Publications

2025

• Parallelized Autoregressive Visual Generation. [PDF] [Project]
  Yuqing Wang, Shuhuai Ren, Zhijie Lin, Yujin Han, Haoyuan Guo, Zhenheng Yang, Difan Zou, Jiashi Feng, Xihui Liu.
  Conference on Computer Vision and Pattern Recognition (CVPR), 2025

• Beyond Surface Structure: A Causal Assessment of LLMs’ Comprehension Ability. [PDF] [Code] [Slide]
  Yujin Han, Lei Xu, Sirui Chen, Difan Zou, Chaochao Lu.
  International Conference on Learning Representations (ICLR), 2025

2024

• Slight Corruption in Pre-training Data Makes Better Diffusion Models. [PDF]
  Hao Chen, Yujin Han, Diganta Misra, Xiang Li, Kai Hu, Difan Zou, Masashi Sugiyama, Jindong Wang, Bhiksha Raj.
  Conference on Advances in Neural Information Processing Systems (NeurIPS), 2024 (Spotlight)

• On the Discrepancy and Connection between Memorization and Generation in Diffusion Models. [PDF]
  Hanyu Wang, Yujin Han, Difan Zou.
  ICML 2024 Workshop on Foundation Models in the Wild, 2024

• Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference. [PDF] [Code] [Slide]
  Yujin Han, Difan Zou.
  NeurIPS Workshop on Causal Representation Learning (CRL), 2023
  International Conference on Machine Learning (ICML), 2024

• Conformalized semi-supervised random forest for classification and abnormality detection. [PDF] [Code]
  Yujin Han^*, Mingwenchan Xu^*, Leying Guan.
  International Conference on Artificial Intelligence and Statistics (AISTATS), 2024

Preprints

• Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images? [Arxiv]
  Yujin Han^*, Andi Han^*, Wei Huang, Chaochao Lu, Difan Zou.

• Masked Autoencoders Are Effective Tokenizers for Diffusion Models. [Arxiv] [Code]
  Hao Chen*, Yujin Han^*, Fangyi Chen, Xiang Li, Yidong Wang, Jindong Wang, Ze Wang, Zicheng Liu, Difan Zou, Bhiksha Raj.