| 2026 | AAAI | GenVidBench: A 6-Million Benchmark for AI-Generated Video Detection. | Zhenliang Ni, Qiangyu Yan, Mouxiao Huang, Tianning Yuan, Yehui Tang, Hailin Hu, Xinghao Chen, Yunhe Wang |
| 2026 | AAAI | PocketLLM: Ultimate Compression of Large Language Models via Meta Networks. | Ye Tian, Chengcheng Wang, Jing Han, Yehui Tang, Kai Han |
| 2026 | ACL | Multi-Granularity Semantic Revision for Large Language Model Distillation. | Xiaoyu Liu, Yun Zhang, Wei Li, Simiao Li, Xudong Huang, Hanting Chen, Yehui Tang, Jie Hu, Zhiwei Xiong, Yunhe Wang |
| 2025 | AAAI | Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts. | Miao Rang, Zhenni Bi, Chuanjian Liu, Yehui Tang, Kai Han, Yunhe Wang |
| 2025 | AAAI | TinySAM: Pushing the Envelope for Efficient Segment Anything Model. | Han Shu, Wenshuo Li, Yehui Tang, Yiman Zhang, Yihao Chen, Houqiang Li, Yunhe Wang, Xinghao Chen |
| 2025 | ICLR | CBQ: Cross-Block Quantization for Large Language Models. | Xin Ding, Xiaoyu Liu, Zhijun Tu, Yun Zhang, Wei Li, Jie Hu, Hanting Chen, Yehui Tang, Zhiwei Xiong, Baoqun Yin, Yunhe Wang |
| 2025 | ICLR | QuaDiM: A Conditional Diffusion Model For Quantum State Property Estimation. | Yehui Tang, Mabiao Long, Junchi Yan |
| 2025 | ICML | LLM Data Selection and Utilization via Dynamic Bi-level Optimization. | Yang Yu, Kai Han, Hang Zhou, Yehui Tang, Kaiqi Huang, Yunhe Wang, Dacheng Tao |
| 2025 | ICML | QEM-Bench: Benchmarking Learning-based Quantum Error Mitigation and QEMFormer as a Multi-ranged Context Learning Baseline. | Tianyi Bao, Ruizhe Zhong, Xinyu Ye, Yehui Tang, Junchi Yan |
| 2025 | ICML | Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning. | Zhenni Bi, Kai Han, Chuanjian Liu, Yehui Tang, Yunhe Wang |
| 2025 | ICML | SlimLLM: Accurate Structured Pruning for Large Language Models. | Jialong Guo, Xinghao Chen, Yehui Tang, Yunhe Wang |
| 2025 | ICML | SpeCache: Speculative Key-Value Caching for Efficient Generation of LLMs. | Shibo Jie, Yehui Tang, Kai Han, Zhi-Hong Deng, Jing Han |
| 2025 | ICML | Mixture of Lookup Experts. | Shibo Jie, Yehui Tang, Kai Han, Yitong Li, Duyu Tang, Zhi-Hong Deng, Yunhe Wang |
| 2025 | IJCAI | Tensor Network: from the Perspective of AI4Science and Science4AI. | Junchi Yan, Yehui Tang, Xinyu Ye, Hao Xiong, Xiaoqiu Zhong, Yuhan Wang, Yuan Qi |
| 2025 | KDD | Reinvent the Operation not the Architecture: Quantum-inspired High-order Product for Compatible and Improved LLMs Training. | Hao Xiong, Yebin Yang, Huaijin Wu, Xiaoqiu Zhong, Yehui Tang, Zhuo Xia, Xiaoxing Wang, Junchi Yan |
| 2025 | NAACL | DenseSSM: State Space Models with Dense Hidden Connection for Efficient Large Language Models. | Wei He, Kai Han, Yehui Tang, Chengcheng Wang, Yujie Yang, Tianyu Guo, Yunhe Wang |
| 2025 | NAACL | EMS-SD: Efficient Multi-sample Speculative Decoding for Accelerating Large Language Models. | Yunsheng Ni, Chuanjian Liu, Yehui Tang, Kai Han, Yunhe Wang |
| 2025 | WWW | GPT4Image: Large Pre-trained Models Help Vision Models Learn Better on Perception Task. | Ning Ding, Yehui Tang, Zhongqian Fu, Chao Xu, Kai Han, Yunhe Wang |
| 2024 | CVPR | 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, Yehui Tang, Xinyu Ye, Junchi Yan |
| 2024 | ECCV | Token Compensator: Altering Inference Cost of Vision Transformer Without Re-tuning. | Shibo Jie, Yehui Tang, Jianyuan Guo, Zhi-Hong Deng, Kai Han, Yunhe Wang |
| 2024 | ECCV | Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation. | Zhenliang Ni, Xinghao Chen, Yingjie Zhai, Yehui Tang, Yunhe Wang |
| 2024 | ECCV | Visual Prompting via Partial Optimal Transport. | Mengyu Zheng, Zhiwei Hao, Yehui Tang, Chang Xu |
| 2024 | ECCV | Adapt Without Forgetting: Distill Proximity from Dual Teachers in Vision-Language Models. | Mengyu Zheng, Yehui Tang, Zhiwei Hao, Kai Han, Yunhe Wang, Chang Xu |
| 2024 | ICLR | Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space. | Hao Xiong, Yehui Tang, Yunlin He, Wei Tan, Junchi Yan |
| 2024 | ICLR | Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark. | Yehui Tang, Hao Xiong, Nianzu Yang, Tailong Xiao, Junchi Yan |
| 2024 | ICML | SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization. | Jialong Guo, Xinghao Chen, Yehui Tang, Yunhe Wang |
| 2024 | ICML | Data-efficient Large Vision Models through Sequential Autoregression. | Zhiwei Hao, Jianyuan Guo, Chengcheng Wang, Yehui Tang, Han Wu, Han Hu, Kai Han, Chang Xu |
| 2024 | ICML | Memory-Space Visual Prompting for Efficient Vision-Language Fine-Tuning. | Shibo Jie, Yehui Tang, Ning Ding, Zhi-Hong Deng, Kai Han, Yunhe Wang |
| 2024 | ICML | ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking. | Wenshuo Li, Xinghao Chen, Han Shu, Yehui Tang, Yunhe Wang |
| 2024 | ICML | Rethinking Optimization and Architecture for Tiny Language Models. | Yehui Tang, Kai Han, Fangcheng Liu, Yunsheng Ni, Yuchuan Tian, Zheyuan Bai, Yi-Qi Hu, Sichao Liu, Shangling Jui, Yunhe Wang |
| 2024 | ICML | SSL4Q: Semi-Supervised Learning of Quantum Data with Application to Quantum State Classification. | Yehui Tang, Nianzu Yang, Mabiao Long, Junchi Yan |
| 2023 | CVPR | Network Expansion For Practical Training Acceleration. | Ning Ding, Yehui Tang, Kai Han, Chao Xu, Yunhe Wang |
| 2023 | CVPR | Masked Image Modeling with Local Multi-Scale Reconstruction. | Haoqing Wang, Yehui Tang, Yunhe Wang, Jianyuan Guo, Zhi-Hong Deng, Kai Han |
| 2022 | CVPR | Source-Free Domain Adaptation via Distribution Estimation. | Ning Ding, Yixing Xu, Yehui Tang, Chao Xu, Yunhe Wang, Dacheng Tao |
| 2022 | CVPR | CMT: Convolutional Neural Networks Meet Vision Transformers. | Jianyuan Guo, Kai Han, Han Wu, Yehui Tang, Xinghao Chen, Yunhe Wang, Chang Xu |
| 2022 | CVPR | Hire-MLP: Vision MLP via Hierarchical Rearrangement. | Jianyuan Guo, Yehui Tang, Kai Han, Xinghao Chen, Han Wu, Chao Xu, Chang Xu, Yunhe Wang |
| 2022 | CVPR | Patch Slimming for Efficient Vision Transformers. | Yehui Tang, Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chao Xu, Dacheng Tao |
| 2022 | CVPR | An Image Patch is a Wave: Phase-Aware Vision MLP. | Yehui Tang, Kai Han, Jianyuan Guo, Chang Xu, Yanxi Li, Chao Xu, Yunhe Wang |
| 2022 | ICML | Spatial-Channel Token Distillation for Vision MLPs. | Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang, Chang Xu |
| 2022 | KDD | Towards a Native Quantum Paradigm for Graph Representation Learning: A Sampling-based Recurrent Embedding Approach. | Ge Yan, Yehui Tang, Junchi Yan |
| 2021 | CVPR | Manifold Regularized Dynamic Network Pruning. | Yehui Tang, Yunhe Wang, Yixing Xu, Yiping Deng, Chao Xu, Dacheng Tao, Chang Xu |
| 2021 | CVPR | ReNAS: Relativistic Evaluation of Neural Architecture Search. | Yixing Xu, Yunhe Wang, Kai Han, Yehui Tang, Shangling Jui, Chunjing Xu, Chang Xu |
| 2021 | ICCV | Homogeneous Architecture Augmentation for Neural Predictor. | Yuqiao Liu, Yehui Tang, Yanan Sun |
| 2020 | AAAI | Beyond Dropout: Feature Map Distortion to Regularize Deep Neural Networks. | Yehui Tang, Yunhe Wang, Yixing Xu, Boxin Shi, Chao Xu, Chunjing Xu, Chang Xu |
| 2020 | AAAI | Reborn Filters: Pruning Convolutional Neural Networks with Limited Data. | Yehui Tang, Shan You, Chang Xu, Jin Han, Chen Qian, Boxin Shi, Chao Xu, Changshui Zhang |
| 2020 | CVPR | Frequency Domain Compact 3D Convolutional Neural Networks. | Hanting Chen, Yunhe Wang, Han Shu, Yehui Tang, Chunjing Xu, Boxin Shi, Chao Xu, Qi Tian, Chang Xu |
| 2020 | CVPR | Neuromorphic Camera Guided High Dynamic Range Imaging. | Jin Han, Chu Zhou, Peiqi Duan, Yehui Tang, Chang Xu, Chao Xu, Tiejun Huang, Boxin Shi |
| 2020 | CVPR | A Semi-Supervised Assessor of Neural Architectures. | Yehui Tang, Yunhe Wang, Yixing Xu, Hanting Chen, Boxin Shi, Chao Xu, Chunjing Xu, Qi Tian, Chang Xu |