Op-CAD: Benchmarking and Investigating Operation-oriented CAD Generation.
Yixue Bai, Yufei Gu, and Zeke Xie#.
In International Conference on Machine Learning. [ICML 2026]
Exploring Data-Free LoRA Transferability for Video Diffusion Models.
Yuchen Wang, Wenliang Zhong, Lichen Bai, Zikai Zhou, Shitong Shao, Bojun Cheng, Shuo Chen, Shuo Yang, and Zeke Xie#.
In International Conference on Machine Learning. [ICML 2026]
Optimizing Few-Step Generation with Adaptive Matching Distillation.
Lichen Bai*, Zikai Zhou*, Wenliang Zhong, Shitong Shao, Shuo Yang, Shuo Chen, Bojun Cheng, and Zeke Xie#.
In International Conference on Machine Learning. [ICML 2026]
LIVEditor-14B: Lightning Unified Video Editor via In-Context Sparse Attention.
Shitong Shao*, Zikai Zhou*, Haopeng Li, Yingwei Song, Wenliang Zhong, Lichen Bai, and Zeke Xie#.
In International Conference on Machine Learning. [ICML 2026][HuggingFace Model][Code][Project Page ][Blog]
Parallelizing Stepwise Momentum for Delta Linear Attention.
Yulong Huang*, Xiang Liu*, Hongxiang Huang, Xiaopeng Lin, Zunchang Liu, Xiaowen Chu, Zeke Xie#, Bojun Cheng#.
In International Conference on Machine Learning. [ICML 2026]
ArcDAE: Asymmetric Rectified Contrastive Diffusion Autoencoder for Unified Representation Learning.
Ge Gao, Shuo Chen, Di Xiong, Zeke Xie, Jian Yang.
In International Conference on Machine Learning. [ICML 2026]
Not All Noises Are Created Equally: Diffusion Noise Selection and Optimization.
Zipeng Qi, Lichen Bai, Haoyi Xiong, and Zeke Xie#.
In IEEE International Conference on Multimedia and Expo. [ICME 2026][Blog][Blog]
A Simple and Efficient Baseline for Zero-Shot Generative Classification.
Zipeng Qi*, Buhua Liu*, Lichen Bai, Zhiqiang Xu, Hu Yang, Haoyi Xiong, and Zeke Xie#.
In IEEE International Conference on Multimedia and Expo. [ICME 2026]
CRAFT: Aligning Diffusion Models with Fine-Tuning Is Easier Than You Think.
Zening Sun*, Zhengpeng Xie*, Lichen Bai, Shitong Shao, Shuo Yang, and Zeke Xie#.
In IEEE/CVF Conference on Computer Vision and Pattern Recognition. [CVPR 2026]
FastLightGen: Fast and Light Video Generation with Fewer Steps and Parameters.
Shitong Shao, Yufei Gu, and Zeke Xie#.
In IEEE/CVF Conference on Computer Vision and Pattern Recognition. [CVPR 2026]
Accelerating Diffusion Model Training under Minimal Budgets: A Condensation-Based Perspective.
Rui Huang*, Shitong Shao*, Zikai Zhou, Pukun Zhao, Hangyu Guo, Tian Ye, Lichen Bai, Shuo Yang, and Zeke Xie#.
In IEEE/CVF Conference on Computer Vision and Pattern Recognition. [CVPR 2026]
DIMOS: Disentangling Instance-level Moving Object Segmentation.
Hongxiang Huang, Hongwei Ren, Xiaopeng LIN, Yulong Huang, Zeke Xie, Bojun Cheng.
In IEEE/CVF Conference on Computer Vision and Pattern Recognition. [CVPR 2026]
Do All Individual Layers Help? An Empirical Study of Task-Interfering Layers in Vision-Language Models.
Zhiming Liu, Yujie Wei, Shuo Yang, Lei Feng, Xiaobo Xia, Zeke Xie, and Liqiang Nie.
In Findings of IEEE/CVF Conference on Computer Vision and Pattern Recognition. [CVPR 2026 Findings]
Weak-to-Strong Diffusion with Reflection.
Lichen Bai, Masashi Sugiyama, and Zeke Xie#.
In International Conference on Learning Representations. [ICLR 2026][Code]
Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation.
Dian Xie*, Shitong Shao*, Lichen Bai, Zikai Zhou, Bojun Cheng, Shuo Yang, Jun Wu, and Zeke Xie#.
In International Conference on Learning Representations. [ICLR 2026]
Late-to-Early Training: Let LLMs Learn Earlier, So Faster and Better.
Ji Zhao, Yufei Gu, Shitong Shao, Xun Zhou, Liang Xiang, and Zeke Xie#.
In International Conference on Learning Representations. [ICLR 2026][Blog]
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics.
Weida Wang, Dongchen Huang, ..., Zeke Xie, ..., and Hongming Weng.
In International Conference on Learning Representations. [ICLR 2026]
AMRM-Pure: Semantic-Preserving Adversarial Purification.
Zhihao Dou, Zhiqiang Gao, Dongfei Cui, Weida Wang, Qinjian Zhao, Dinggen Zhang, Jun Yan, Zeke Xie, Shufei Zhang
In International Conference on Artificial Intelligence and Statistics. [AISTATS 2026, Spotlight]
Channel Matters: Estimating Channel Influence for Multivariate Time Series.
Muyao Wang, Zeke Xie#, Bo Chen#, Hongwei Liu, and James Kwok.
In Neural Information Processing Systems. [NeurIPS 2025]
UtilGen: Utility-Centric Generative Data Augmentation with Dual-Level Task Adaptation.
Jiyu Guo, Shuo Yang, Yiming Huang, Yancheng Long, Xiaobo Xia, Xiu Su, Bo Zhao, Zeke Xie, and Liqiang Nie..
In Neural Information Processing Systems. [NeurIPS 2025]
Golden Noise for Diffusion Models: A Learning Framework.
Zikai Zhou, Shitong Shao, Lichen Bai, Shufei Zhang, Zhiqiang Xu, Bo Han, and Zeke Xie#.
In International Conference on Computer Vision. [ICCV 2025][Blog][Code]
Investigating the Overlooked Hessian Structure: From CNNs to LLMs.
Qian-Yuan Tang*, Yufei Gu*, Yunfeng Cai, Mingming Sun, Ping Li, Xun Zhou, and Zeke Xie#.
In International Conference on Machine Learning. [ICML 2025]
Principled Data Selection for Alignment: The Hidden Risks of Difficult Examples.
Chengqian Gao, Haonan Li, Liu Liu, Zeke Xie, Peilin Zhao, and Zhiqiang Xu.
In International Conference on Machine Learning. [ICML 2025]
Mono2Stereo: A Benchmark and Empirical Study for Stereo Conversion.
Songsong Yu, Yuxin Chen, Zhongang Qi, Zeke Xie, Yifan Wang, Lijun Wang, Ying Shan, and Huchuan Lu.
In IEEE/CVF Conference on Computer Vision and Pattern Recognition. [CVPR 2025]
Learning from Ambiguous Data with Hard Labels.
Zeke Xie#*, Zheng He*, Nan Lu*, Lichen Bai, Bao Li, Shuo Yang, Mingming Sun, and Ping Li.
In IEEE International Conference on Acoustics, Speech, and Signal Processing. [ICASSP 2025]
Diffusion Models are Zero-Shot Generative Text-Vision Retrievers.
Bao Li*, Zeke Xie*, Xiaomei Zhang, Xiangyu Zhu, and Zhen Lei.
In IEEE International Conference on Acoustics, Speech, and Signal Processing. [ICASSP 2025, Oral]
Stronger Separability, Stronger Defense: Influence-based Backdoor Detection.
Buhua Liu, Shuo Yang, Zhiqiang Xu, Haoyi Xiong, Yiu-ming Cheung, and Zeke Xie#.
In Pacific-Asia Conference on Knowledge Discovery and Data Mining. [PAKDD 2025]
IV-mixed Sampler: Leveraging Image Diffusion Model for Enhanced Video Synthesis.
Shitong Shao*, Zikai Zhou*, Lichen Bai, Haoyi Xiong, and Zeke Xie#.
In International Conference on Learning Representations. [ICLR 2025][Project Page][Blog]
Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection.
Lichen Bai, Shitong Shao, Zikai Zhou, Zipeng Qi, Zhiqiang Xu, Haoyi Xiong, and Zeke Xie#.
In International Conference on Learning Representations. [ICLR 2025][Blog][Media][Media][Code]
Neural Field Classifiers via Target Encoding and Classification Loss.
Xindi Yang*, Zeke Xie#*, Xiong Zhou, Boyu Liu, Buhua Liu, Yi Liu, Haoran Wang, Yunfeng Cai, and Mingming Sun.
In International Conference on Learning Representations. [ICLR 2024]
Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data.
Xiong Zhou, Xianming Liu, Hao Yu, Jialiang Wang, Zeke Xie, Junjun Jiang, and Xiangyang Ji.
In International Conference on Learning Representations. [ICLR 2024]
On the Overlooked Structure of Stochastic Gradients.
Zeke Xie, Qian-Yuan Tang, Mingming Sun, and Ping Li.
In Neural Information Processing Systems. [NeurIPS 2023]
On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective.
Zeke Xie, Zhiqiang Xu, Jingzhao Zhang, Issei Sato, and Masashi Sugiyama.
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S3IM: Stochastic Structural SIMilarity and Its Unreasonable Effectiveness for Neural Fields.
Zeke Xie*, Xindi Yang*, Yujie Yang, Qi Sun, Yixiang Jiang, Haoran Wang, Yi Liu, Yunfeng Cai, and Mingming Sun.
In International Conference on Computer Vision. [ICCV 2023][Blog][Media][Media][Media][Media][Media]
Dataset Pruning: Reducing Training Data by Examining Generalization Influence.
Shuo Yang, Zeke Xie, Hanyu Peng, Min Xu, Mingming Sun, and Ping Li.
In International Conference on Learning Representations. [ICLR 2023]
Sparse Double Descent: Where Network Pruning Aggravates Overfitting.
Zheng He, Zeke Xie, Quanzhi Zhu, and Zengchang Qin.
In International Conference on Machine Learning. [ICML 2022][Blog]
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum.
Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, and Masashi Sugiyama.
In International Conference on Machine Learning. [ICML 2022, Oral, 2%][Blog][Media][Media]
Positive-Negative Momentum: Manipulating Stochastic Gradient Noise to Improve Generalization.
Zeke Xie, Li Yuan, Zhanxing Zhu, and Masashi Sugiyama.
In International Conference on Machine Learning. [ICML 2021]
A Diffusion Theory For Deep Learning Dynamics: Stochastic Gradient Descent Exponentially Favors Flat Minima.
Zeke Xie, Issei Sato, and Masashi Sugiyama.
In International Conference on Learning Representations. [ICLR 2021][Blog][Blog][Media]
DSADF: Thinking Fast and Slow for Decision Making.
Alex Zhihao Dou, Dongfei Cui, Jun Yan, Weida Wang, Benteng Chen, Haoming Wang, Zeke Xie, and Shufei Zhang.
In International Journal of Computer Vision. [IJCV 2026][IF: 9.3]
Improved and Accelerated Text-to-Image Generation with Collect, Reflect, and Refine.
Shitong Shao, Zikai Zhou, Dian Xie, Yuetong Fang, Tian Ye, Lichen Bai, Bo Han, and Zeke Xie#.
In IEEE Transactions on Pattern Analysis and Machine Intelligence. [TPAMI 2026][IF: 18.6][Code]
Understanding Data Influence with Differential Approximation.
Haoru Tan, Sitong Wu, Xiuzhe Wu, Wang Wang, Bo Zhao, Zeke Xie, Gui-Song Xia, and Xiaojuan Qi.
In IEEE Transactions on Pattern Analysis and Machine Intelligence. [TPAMI 2026][IF: 18.6]
Alignment of Diffusion Models: Fundamentals, Challenges, and Future.
Buhua Liu, Shitong Shao, Bao Li, Lichen Bai, Zhiqiang Xu, Haoyi Xiong, James Kwok, Sumi Helal, and Zeke Xie#.
In ACM Computing Surveys. [CSUR 2026][IF: 28.0]
Pre-trained Molecular Language Models with Random Functional Group Masking.
Tianhao Peng , Yuchen Li, Xuhong Li , Jiang Bian, Zeke Xie, Ning Sui, Shahid Mumtaz, Yanwu Xu, Linghe Kong, and Haoyi Xiong.
In npj Artificial Intelligence, Springer Nature Press. [npj AI 2025]
Noisy Correspondence Rectification in Multimodal Clustering Space for Cross-Modal Matching.
Shuo Yang, Yancheng Long, Yujie Wei, Zeke Xie, Hongxun Yao, Min Xu, Liqiang Nie.
In IEEE Transactions on Pattern Analysis and Machine Intelligence. [TPAMI 2025][IF: 18.6]
Artificial Neural Variability for Deep Learning: On Overfitting, Noise Memorization, and Catastrophic Forgetting.
Zeke Xie, Fengxiang He, Shaopeng Fu, Issei Sato, Dacheng Tao, and Masashi Sugiyama.
In Neural Computation, MIT Press. [NECO 2021]