Bringing Giant Neural Networks Down to Earth with Unlabeled Data. - Yehui Tang; Shan You; Chang Xu 002; Boxin Shi; Chao Xu 006 (CoRR, 2019)

RNAS: Architecture Ranking for Powerful Networks. - Yixing Xu; Yunhe Wang 001; Kai Han 002; Hanting Chen; Yehui Tang; Shangling Jui; Chunjing Xu; Qi Tian 001; Chang Xu 002 (CoRR, 2019)

Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks. - Yehui Tang; Yunhe Wang 001; Yixing Xu; Boxin Shi; Chao Xu 006; Chunjing Xu; Chang Xu 002 (AAAI, 2020)

Reborn Filters: Pruning Convolutional Neural Networks with Limited Data. - Yehui Tang; Shan You; Chang Xu 002; Jin Han 001; Chen Qian 006; Boxin Shi; Chao Xu 006; Changshui Zhang (AAAI, 2020)

Frequency Domain Compact 3D Convolutional Neural Networks. - Hanting Chen; Yunhe Wang 001; Han Shu; Yehui Tang; Chunjing Xu; Boxin Shi; Chao Xu 006; Qi Tian 001; Chang Xu 002 (CVPR, 2020)

Neuromorphic Camera Guided High Dynamic Range Imaging. - Jin Han 001; Chu Zhou; Peiqi Duan; Yehui Tang; Chang Xu 002; Chao Xu 006; Tiejun Huang 001; Boxin Shi (CVPR, 2020)

A Semi-Supervised Assessor of Neural Architectures. - Yehui Tang; Yunhe Wang 001; Yixing Xu; Hanting Chen; Boxin Shi; Chao Xu 006; Chunjing Xu; Qi Tian 001; Chang Xu 002 (CVPR, 2020)

SCOP: Scientific Control for Reliable Neural Network Pruning. - Yehui Tang; Yunhe Wang 001; Yixing Xu; Dacheng Tao; Chunjing Xu; Chao Xu 006; Chang Xu 002 (NeurIPS, 2020)

A Survey on Visual Transformer. - Kai Han 002; Yunhe Wang 001; Hanting Chen; Xinghao Chen 001; Jianyuan Guo; Zhenhua Liu 003; Yehui Tang; An Xiao; Chunjing Xu; Yixing Xu; Zhaohui Yang 003; Yiman Zhang; et al. (CoRR, 2020)

Manifold Regularized Dynamic Network Pruning. - Yehui Tang; Yunhe Wang 001; Yixing Xu; Yiping Deng; Chao Xu 006; Dacheng Tao; Chang Xu 002 (CVPR, 2021)

ReNAS: Relativistic Evaluation of Neural Architecture Search. - Yixing Xu; Yunhe Wang 001; Kai Han 002; Yehui Tang; Shangling Jui; Chunjing Xu; Chang Xu 002 (CVPR, 2021)

Homogeneous Architecture Augmentation for Neural Predictor. - Yuqiao Liu 002; Yehui Tang; Yanan Sun 001 (ICCV, 2021)

Augmented Shortcuts for Vision Transformers. - Yehui Tang; Kai Han 002; Chang Xu 002; An Xiao; Yiping Deng; Chao Xu 006; Yunhe Wang 001 (NeurIPS, 2021)

Learning Frequency Domain Approximation for Binary Neural Networks. - Yixing Xu; Kai Han 002; Chang Xu 002; Yehui Tang; Chunjing Xu; Yunhe Wang 001 (NeurIPS, 2021)

Visual Transformer Pruning. - Mingjian Zhu; Kai Han 002; Yehui Tang; Yunhe Wang 001 (CoRR, 2021)

Efficient Vision Transformers via Fine-Grained Manifold Distillation. - Ding Jia; Kai Han 002; Yunhe Wang 001; Yehui Tang; Jianyuan Guo; Chao Zhang 001; Dacheng Tao (CoRR, 2021)

CMT: Convolutional Neural Networks Meet Vision Transformers. - Jianyuan Guo; Kai Han 002; Han Wu 009; Chang Xu 002; Yehui Tang; Chunjing Xu; Yunhe Wang 001 (CoRR, 2021)

Source-Free Domain Adaptation via Distribution Estimation. - Ning Ding; Yixing Xu; Yehui Tang; Chao Xu 006; Yunhe Wang 001; Dacheng Tao (CVPR, 2022)

CMT: Convolutional Neural Networks Meet Vision Transformers. - Jianyuan Guo; Kai Han 002; Han Wu 009; Yehui Tang; Xinghao Chen 001; Yunhe Wang 001; Chang Xu 002 (CVPR, 2022)

Hire-MLP: Vision MLP via Hierarchical Rearrangement. - Jianyuan Guo; Yehui Tang; Kai Han 002; Xinghao Chen 001; Han Wu 009; Chao Xu 006; Chang Xu 002; Yunhe Wang 001 (CVPR, 2022)

Patch Slimming for Efficient Vision Transformers. - Yehui Tang; Kai Han 002; Yunhe Wang 001; Chang Xu 002; Jianyuan Guo; Chao Xu 006; Dacheng Tao (CVPR, 2022)

An Image Patch is a Wave: Phase-Aware Vision MLP. - Yehui Tang; Kai Han 002; Jianyuan Guo; Chang Xu 002; Yanxi Li 001; Chao Xu 006; Yunhe Wang 001 (CVPR, 2022)

Spatial-Channel Token Distillation for Vision MLPs. - Yanxi Li 001; Xinghao Chen 001; Minjing Dong; Yehui Tang; Yunhe Wang 001; Chang Xu 002 (ICML, 2022)

Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach. - Ge Yan 001; Yehui Tang; Junchi Yan (KDD, 2022)

Vision GNN: An Image is Worth Graph of Nodes. - Kai Han 002; Yunhe Wang 001; Jianyuan Guo; Yehui Tang; Enhua Wu (NeurIPS, 2022)

Bridge the Gap Between Architecture Spaces via A Cross-Domain Predictor. - Yuqiao Liu 002; Yehui Tang; Zeqiong Lv; Yunhe Wang 001; Yanan Sun 001 (NeurIPS, 2022)

Learning Efficient Vision Transformers via Fine-Grained Manifold Distillation. - Zhiwei Hao; Jianyuan Guo; Ding Jia; Kai Han 002; Yehui Tang; Chao Zhang 001; Han Hu 001; Yunhe Wang 001 (NeurIPS, 2022)

GhostNetV2: Enhance Cheap Operation with Long-Range Attention. - Yehui Tang; Kai Han 002; Jianyuan Guo; Chang Xu 002; Chao Xu 006; Yunhe Wang 001 (NeurIPS, 2022)

GraphQNTK: Quantum Neural Tangent Kernel for Graph Data. - Yehui Tang; Junchi Yan (NeurIPS, 2022)

PyramidTNT: Improved Transformer-in-Transformer Baselines with Pyramid Architecture. - Kai Han 002; Jianyuan Guo; Yehui Tang; Yunhe Wang 001 (CoRR, 2022)

From Quantum Graph Computing to Quantum Graph Learning: A Survey. - Yehui Tang; Junchi Yan; Edwin R. Hancock (CoRR, 2022)

FastMIM: Expediting Masked Image Modeling Pre-training for Vision. - Jianyuan Guo; Kai Han 002; Han Wu 009; Yehui Tang; Yunhe Wang 001; Chang Xu 002 (CoRR, 2022)

Recent progress and perspectives on quantum computing for finance. - Yehui Tang; Junchi Yan; Guoqiang Hu; Baohua Zhang; Jinzan Zhou (Serv. Oriented Comput. Appl., 2022)

Network Expansion For Practical Training Acceleration. - Ning Ding; Yehui Tang; Kai Han 002; Chao Xu 006; Yunhe Wang 001 (CVPR, 2023)

Masked Image Modeling with Local Multi-Scale Reconstruction. - Haoqing Wang; Yehui Tang; Yunhe Wang 001; Jianyuan Guo; Zhi-Hong Deng 001; Kai Han 002 (CVPR, 2023)

One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation. - Zhiwei Hao; Jianyuan Guo; Kai Han 002; Yehui Tang; Han Hu 001; Yunhe Wang 001; Chang Xu 002 (NeurIPS, 2023)

GPT4Image: Can Large Pre-trained Models Help Vision Models on Perception Tasks? - Ning Ding; Yehui Tang; Zhongqian Fu; Chao Xu 006; Kai Han 002; Yunhe Wang 001 (CoRR, 2023)

LightCLIP: Learning Multi-Level Interaction for Lightweight Vision-Language Models. - Ying Nie; Wei He 001; Kai Han 002; Yehui Tang; Tianyu Guo 001; Fanyi Du; Yunhe Wang 001 (CoRR, 2023)

PanGu-π: Enhancing Language Model Architectures via Nonlinearity Compensation. - Yunhe Wang 001; Hanting Chen; Yehui Tang; Tianyu Guo 001; Kai Han 002; Ying Nie; Xutao Wang; Hailin Hu 002; Zheyuan Bai; Yun Wang; Fangcheng Liu; Zhicheng Liu 001; et al. (CoRR, 2023)

A Survey on Vision Transformer. - Kai Han 002; Yunhe Wang 001; Hanting Chen; Xinghao Chen 001; Jianyuan Guo; Zhenhua Liu 003; Yehui Tang; An Xiao; Chunjing Xu; Yixing Xu; Zhaohui Yang 003; Yiman Zhang; et al. (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine Learning. - Hao Xiong 003; Yehui Tang; Xinyu Ye; Junchi Yan (CVPR, 2024)

Token Compensator: Altering Inference Cost of Vision Transformer Without Re-tuning. - Shibo Jie; Yehui Tang; Jianyuan Guo; Zhi-Hong Deng 001; Kai Han 002; Yunhe Wang 001 (ECCV (16), 2024)

Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation. - Zhenliang Ni; Xinghao Chen 001; Yingjie Zhai; Yehui Tang; Yunhe Wang 001 (ECCV (52), 2024)

Visual Prompting via Partial Optimal Transport. - Mengyu Zheng; Zhiwei Hao; Yehui Tang; Chang Xu 002 (ECCV (35), 2024)

Adapt Without Forgetting: Distill Proximity from Dual Teachers in Vision-Language Models. - Mengyu Zheng; Yehui Tang; Zhiwei Hao; Kai Han 002; Yunhe Wang 001; Chang Xu 002 (ECCV (54), 2024)

Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space. - Hao Xiong 003; Yehui Tang; Yunlin He; Wei Tan; Junchi Yan (ICLR, 2024)

Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark. - Yehui Tang; Hao Xiong 003; Nianzu Yang; Tailong Xiao; Junchi Yan (ICLR, 2024)

SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization. - Jialong Guo; Xinghao Chen 001; Yehui Tang; Yunhe Wang 001 (ICML, 2024)

Data-efficient Large Vision Models through Sequential Autoregression. - Zhiwei Hao; Jianyuan Guo; Chengcheng Wang; Yehui Tang; Han Wu 009; Han Hu 001; Kai Han 002; Chang Xu 002 (ICML, 2024)

Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning. - Shibo Jie; Yehui Tang; Ning Ding; Zhi-Hong Deng 001; Kai Han 002; Yunhe Wang 001 (ICML, 2024)

ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking. - Wenshuo Li; Xinghao Chen 001; Han Shu; Yehui Tang; Yunhe Wang 001 (ICML, 2024)

Rethinking Optimization and Architecture for Tiny Language Models. - Yehui Tang; Kai Han 002; Fangcheng Liu; Yunsheng Ni; Yuchuan Tian; Zheyuan Bai; Yi-Qi Hu; Sichao Liu; Shangling Jui; Yunhe Wang 001 (ICML, 2024)

SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification. - Yehui Tang; Nianzu Yang; Mabiao Long; Junchi Yan (ICML, 2024)

MemoryFormer : Minimize Transformer Computation by Removing Fully-Connected Layers. - Ning Ding; Yehui Tang; Haochen Qin; Zhenli Zhou; Chao Xu 006; Lin Li; Kai Han 002; Heng Liao; Yunhe Wang 001 (NeurIPS, 2024)

Kangaroo: Lossless Self-Speculative Decoding for Accelerating LLMs via Double Early Exiting. - Fangcheng Liu; Yehui Tang; Zhenhua Liu 003; Yunsheng Ni; Duyu Tang; Kai Han 002; Yunhe Wang 001 (NeurIPS, 2024)

Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning. - Hang Zhou; Yehui Tang; Haochen Qin; Yujie Yang; Renren Jin; Deyi Xiong; Kai Han 002; Yunhe Wang 001 (NeurIPS, 2024)

A Survey on Transformer Compression. - Yehui Tang; Yunhe Wang 001; Jianyuan Guo; Zhijun Tu; Kai Han 002; Hailin Hu 002; Dacheng Tao (CoRR, 2024)

SAM-DiffSR: Structure-Modulated Diffusion Model for Image Super-Resolution. - Chengcheng Wang; Zhiwei Hao; Yehui Tang; Jianyuan Guo; Yujie Yang; Kai Han 002; Yunhe Wang 001 (CoRR, 2024)

DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models. - Wei He 001; Kai Han 002; Yehui Tang; Chengcheng Wang; Yujie Yang; Tianyu Guo 001; Yunhe Wang 001 (CoRR, 2024)

GhostNetV3: Exploring the Training Strategies for Compact Models. - Zhenhua Liu 003; Zhiwei Hao; Kai Han 002; Yehui Tang; Yunhe Wang 001 (CoRR, 2024)

Kangaroo: Lossless Self-Speculative Decoding via Double Early Exiting. - Fangcheng Liu; Yehui Tang; Zhenhua Liu 003; Yunsheng Ni; Kai Han 002; Yunhe Wang 001 (CoRR, 2024)

No Time to Waste: Squeeze Time into Channel for Mobile Video Understanding. - Yingjie Zhai; Wenshuo Li; Yehui Tang; Xinghao Chen 001; Yunhe Wang 001 (CoRR, 2024)

Multi-Granularity Semantic Revision for Large Language Model Distillation. - Xiaoyu Liu; Yun Zhang; Wei Li 002; Simiao Li; Xudong Huang; Hanting Chen; Yehui Tang; Jie Hu 021; Zhiwei Xiong; Yunhe Wang 001 (CoRR, 2024)

Free Video-LLM: Prompt-guided Visual Perception for Efficient Training-free Video LLMs. - Kai Han 002; Jianyuan Guo; Yehui Tang; Wei He 001; Enhua Wu; Yunhe Wang 001 (CoRR, 2024)

Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning. - Zhenni Bi; Kai Han 002; Chuanjian Liu; Yehui Tang; Yunhe Wang 001 (CoRR, 2024)

Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts. - Miao Rang; Zhenni Bi; Chuanjian Liu; Yehui Tang; Kai Han 002; Yunhe Wang 001 (AAAI, 2025)

TinySAM: Pushing the Envelope for Efficient Segment Anything Model. - Han Shu; Wenshuo Li; Yehui Tang; Yiman Zhang; Yihao Chen; Houqiang Li; Yunhe Wang 001; Xinghao Chen 001 (AAAI, 2025)

CBQ: Cross-Block Quantization for Large Language Models. - Xin Ding; Xiaoyu Liu; Zhijun Tu; Yun Zhang; Wei Li 002; Jie Hu 021; Hanting Chen; Yehui Tang; Zhiwei Xiong; Baoqun Yin; Yunhe Wang 001 (ICLR, 2025)

QuaDiM: A Conditional Diffusion Model For Quantum State Property Estimation. - Yehui Tang; Mabiao Long; Junchi Yan (ICLR, 2025)

DenseSSM: State Space Models with Dense Hidden Connection for Efficient Large Language Models. - Wei He 001; Kai Han 002; Yehui Tang; Chengcheng Wang; Yujie Yang; Tianyu Guo 001; Yunhe Wang 001 (NAACL (Long Papers), 2025)

EMS-SD: Efficient Multi-sample Speculative Decoding for Accelerating Large Language Models. - Yunsheng Ni; Chuanjian Liu; Yehui Tang; Kai Han 002; Yunhe Wang 001 (NAACL (Long Papers), 2025)

GPT4Image: Large Pre-trained Models Help Vision Models Learn Better on Perception Task. - Ning Ding; Yehui Tang; Zhongqian Fu; Chao Xu 006; Kai Han 002; Yunhe Wang 001 (WWW (Companion Volume), 2025)

GenVidBench: A Challenging Benchmark for Detecting AI-Generated Video. - Zhenliang Ni; Qiangyu Yan; Mouxiao Huang; Tianning Yuan; Yehui Tang; Hailin Hu 002; Xinghao Chen 001; Yunhe Wang 001 (CoRR, 2025)

Rethinking Video Tokenization: A Conditioned Diffusion-based Approach. - Nianzu Yang; Pandeng Li; Liming Zhao; Yang Li 197; Chen-Wei Xie; Yehui Tang; Xudong Lu; Zhihang Liu; Yun Zheng; Yu Liu 015; Junchi Yan (CoRR, 2025)

Post-Training Quantization for Diffusion Transformer via Hierarchical Timestep Grouping. - Ning Ding; Jing Han; Yuchuan Tian; Chao Xu 006; Kai Han 002; Yehui Tang (CoRR, 2025)

Mixture of Lookup Experts. - Shibo Jie; Yehui Tang; Kai Han 002; Yitong Li; Duyu Tang; Zhi-Hong Deng 001; Yunhe Wang 001 (CoRR, 2025)

SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs. - Shibo Jie; Yehui Tang; Kai Han 002; Zhi-Hong Deng 001; Jing Han (CoRR, 2025)

Saliency-driven Dynamic Token Pruning for Large Language Models. - Yao Tao; Yehui Tang; Yun Wang; Mingjian Zhu; Hailin Hu 002; Yunhe Wang 001 (CoRR, 2025)

Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs. - Yichun Yin; Wenyong Huang; Kaikai Song; Yehui Tang; Xueyu Wu; Wei Guo 006; Peng Guo; Yaoyuan Wang; Xiaojun Meng; Yasheng Wang; Dong Li 016; Can Chen; et al. (CoRR, 2025)

Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUs. - Yehui Tang; Yichun Yin; Yaoyuan Wang; Hang Zhou; Yu Pan; Wei Guo 006; Zhiguo Zhang; Miao Rang; Fangcheng Liu; Naifu Zhang; Binghan Li; Yonghan Dong; et al. (CoRR, 2025)

Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs. - Hanting Chen; Jiarui Qin; Jialong Guo; Tao Yuan; Yichun Yin; Huiling Zhen; Yasheng Wang; Jinpeng Li 004; Xiaojun Meng; Meng Zhang; Rongju Ruan; Zheyuan Bai; et al. (CoRR, 2025)

Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity. - Yehui Tang; Xiaosong Li; Fangcheng Liu; Wei Guo 006; Hang Zhou; Yaoyuan Wang; Kai Han 002; Xianzhi Yu; Jinpeng Li 004; Hui Zang; Fei Mi; Xiaojun Meng; et al. (CoRR, 2025)

Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition. - Hanting Chen; Yasheng Wang; Kai Han 002; Dong Li 016; Lin Li; Zhenni Bi; Jinpeng Li 004; Haoyu Wang 003; Fei Mi; Mingjian Zhu; Bin Wang 027; Kaikai Song; et al. (CoRR, 2025)

SlimLLM: Accurate Structured Pruning for Large Language Models. - Jialong Guo; Xinghao Chen 001; Yehui Tang; Yunhe Wang 001 (CoRR, 2025)

EAQuant: Enhancing Post-Training Quantization for MoE Models via Expert-Aware Optimization. - Zhongqian Fu; Ning Ding; Kai Han 002; Xianzhi Yu; Xiaosong Li; Xinghao Chen 001; Yehui Tang; Yunhe Wang 001 (CoRR, 2025)

DualTHOR: A Dual-Arm Humanoid Simulation Platform for Contingency-Aware Planning. - Boyu Li 003; Siyuan He; Hang Xu; Haoqi Yuan; Yu Zang; Liwei Hu; Junpeng Yue; Zhenxiong Jiang; Pengbo Hu; Börje F. Karlsson; Yehui Tang; Zongqing Lu 002 (CoRR, 2025)

LLM Data Selection and Utilization via Dynamic Bi-level Optimization. - Yang Yu 056; Kai Han 002; Hang Zhou; Yehui Tang; Kaiqi Huang; Yunhe Wang 001; Dacheng Tao (CoRR, 2025)