Boosting Certified 𝓁∞ Robustness with EMA Method and Ensemble Model. - Binghui Li; Shiji Xin; Qizhe Zhang (CoRR, 2021)

Unsupervised Spike Depth Estimation via Cross-modality Cross-domain Knowledge Transfer. - Jiaming Liu 003; Qizhe Zhang; Jianing Li 001; Ming Lu; Tiejun Huang 001; Shanghang Zhang (CoRR, 2022)

Exploring Sparse Visual Prompt for Cross-domain Semantic Segmentation. - Senqiao Yang; Jiarui Wu; Jiaming Liu 003; Xiaoqi Li 009; Qizhe Zhang; Mingjie Pan; Yulu Gan; Shanghang Zhang (CoRR, 2023)

Split & Merge: Unlocking the Potential of Visual Adapters via Sparse Training. - Qizhe Zhang; Bocheng Zou; Ruichuan An; Jiaming Liu 003; Shanghang Zhang (CoRR, 2023)

Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation. - Jiaming Liu 003; Ran Xu 013; Senqiao Yang; Renrui Zhang; Qizhe Zhang; Zehui Chen; Yandong Guo; Shanghang Zhang (CoRR, 2023)

Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction. - Senqiao Yang; Jiarui Wu; Jiaming Liu 003; Xiaoqi Li 009; Qizhe Zhang; Mingjie Pan; Yulu Gan; Zehui Chen; Shanghang Zhang (AAAI, 2024)

Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation. - Jiaming Liu 003; Ran Xu 013; Senqiao Yang; Renrui Zhang; Qizhe Zhang; Zehui Chen; Yandong Guo; Shanghang Zhang (CVPR, 2024)

Gradient-based Parameter Selection for Efficient Fine-Tuning. - Zhi Zhang 009; Qizhe Zhang; Zijun Gao; Renrui Zhang; Ekaterina Shutova; Shiji Zhou; Shanghang Zhang (CVPR, 2024)

Unsupervised Spike Depth Estimation via Cross-modality Cross-domain Knowledge Transfer. - Jiaming Liu 003; Qizhe Zhang; Xiaoqi Li 020; Jianing Li 001; Guanqun Wang; Ming Lu; Tiejun Huang 001; Shanghang Zhang (ICRA, 2024)

Discovering Long-Term Effects on Parameter Efficient Fine-tuning. - Gaole Dai; Yiming Tang; Chunkai Fan; Qizhe Zhang; Zhi Zhang 009; Yulu Gan; Chengqing Zeng; Shanghang Zhang; Tiejun Huang 001 (CoRR, 2024)

Proactive Gradient Conflict Mitigation in Multi-Task Learning: A Sparse Training Perspective. - Zhi Zhang 009; Jiayi Shen; Congfeng Cao; Gaole Dai; Shiji Zhou; Qizhe Zhang; Shanghang Zhang; Ekaterina Shutova (CoRR, 2024)

[CLS] Attention is All You Need for Training-Free Visual Token Pruning: Make VLM Inference Faster. - Qizhe Zhang; Aosong Cheng; Ming Lu; Zhiyong Zhuo; Minqi Wang; Jiajun Cao; Shaobo Guo; Qi She; Shanghang Zhang (CoRR, 2024)

MoVE-KD: Knowledge Distillation for VLMs with Mixture of Visual Encoders. - Jiajun Cao; Yuan Zhang 020; Tao Huang 020; Ming Lu; Qizhe Zhang; Ruichuan An; Ningning Ma; Shanghang Zhang (CVPR, 2025)

Concept-as-Tree: Synthetic Data is All You Need for VLM Personalization. - Ruichuan An; Kai Zeng; Ming Lu; Sihan Yang; Renrui Zhang; Huitong Ji; Qizhe Zhang; Yulin Luo; Hao Liang; Wentao Zhang (CoRR, 2025)

Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs. - Qizhe Zhang; Mengzhen Liu; Lichen Li; Ming Lu; Yuan Zhang 020; Junwen Pan; Qi She; Shanghang Zhang (CoRR, 2025)

FastDriveVLA: Efficient End-to-End Driving via Plug-and-Play Reconstruction-based Token Pruning. - Jiajun Cao; Qizhe Zhang; Peidong Jia; Xuhui Zhao; Bo Lan; Xiaoan Zhang; Xiaobao Wei; Sixiang Chen; Zhuo Li; Yang Wang; Liyun Li; Xianming Liu; et al. (CoRR, 2025)