DAWN: Dual Augmented Memory Network for Unsupervised Video Object Tracking. - Zhenmei Shi; Haoyang Fang; Yu-Wing Tai; Chi-Keung Tang (CoRR, 2019)

SF-Net: Structured Feature Network for Continuous Sign Language Recognition. - Zhaoyang Yang; Zhenmei Shi; Xiaoyong Shen; Yu-Wing Tai (CoRR, 2019)

A Theoretical Analysis on Feature Learning in Neural Networks: Emergence from Inputs and Advantage over Fixed Features. - Zhenmei Shi; Junyi Wei; Yingyu Liang (ICLR, 2022)

Deep Online Fused Video Stabilization. - Zhenmei Shi; Fuhao Shi; Wei-Sheng Lai; Chia-Kai Liang; Yingyu Liang (WACV, 2022)

Attentive Walk-Aggregating Graph Neural Networks. - Mehmet Furkan Demirel; Shengchao Liu; Siddhant Garg; Zhenmei Shi; Yingyu Liang (Trans. Mach. Learn. Res., 2022)

The Trade-off between Universality and Label Efficiency of Representations from Contrastive Learning. - Zhenmei Shi; Jiefeng Chen 001; Kunyang Li 001; Jayaram Raghuram; Xi Wu 001; Yingyu Liang; Somesh Jha (ICLR, 2023)

When and How Does Known Class Help Discover Unknown Ones? Provable Understanding Through Spectral Analysis. - Yiyou Sun; Zhenmei Shi; Yingyu Liang; Yixuan Li 001 (ICML, 2023)

Provable Guarantees for Neural Networks via Gradient Feature Learning. - Zhenmei Shi; Junyi Wei; Yingyu Liang (NeurIPS, 2023)

A Graph-Theoretic Framework for Understanding Open-World Semi-Supervised Learning. - Yiyou Sun; Zhenmei Shi; Yixuan Li 001 (NeurIPS, 2023)

Domain Generalization via Nuclear Norm Regularization. - Zhenmei Shi; Yifei Ming; Ying Fan; Frederic Sala; Yingyu Liang (CPAL, 2024)

Towards Few-Shot Adaptation of Foundation Models via Multitask Finetuning. - Zhuoyan Xu; Zhenmei Shi; Junyi Wei; Fangzhou Mu; Yin Li 003; Yingyu Liang (ICLR, 2024)

Why Larger Language Models Do In-context Learning Differently? - Zhenmei Shi; Junyi Wei; Zhuoyan Xu; Yingyu Liang (ICML, 2024)

Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models. - Jiayu Wang; Yifei Ming; Zhenmei Shi; Vibhav Vineet; Xin Wang 066; Sharon Li 001; Neel Joshi (NeurIPS, 2024)

Fourier Circuits in Neural Networks: Unlocking the Potential of Large Language Models in Mathematical Reasoning and Modular Arithmetic. - Jiuxiang Gu; Chenyang Li; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Tianyi Zhou 011 (CoRR, 2024)

Exploring the Frontiers of Softmax: Provable Optimization, Applications in Diffusion Model, and Beyond. - Jiuxiang Gu; Chenyang Li; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2024)

Conv-Basis: A New Paradigm for Efficient Attention Inference and Gradient Computation in Transformers. - Jiuxiang Gu; Yingyu Liang; Heshan Liu; Zhenmei Shi; Zhao Song 002; Junze Yin (CoRR, 2024)

Tensor Attention Training: Provably Efficient Learning of Higher-order Transformers. - Jiuxiang Gu; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (CoRR, 2024)

Unraveling the Smoothness Properties of Diffusion Models: A Gaussian Mixture Perspective. - Jiuxiang Gu; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (CoRR, 2024)

Toward Infinite-Long Prefix in Transformer. - Jiuxiang Gu; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Chiwun Yang (CoRR, 2024)

Is A Picture Worth A Thousand Words? Delving Into Spatial Reasoning for Vision Language Models. - Jiayu Wang; Yifei Ming; Zhenmei Shi; Vibhav Vineet; Xin Wang; Neel Joshi (CoRR, 2024)

Differential Privacy of Cross-Attention with Provable Guarantee. - Jiuxiang Gu; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (CoRR, 2024)

Do Large Language Models Have Compositional Ability? An Investigation into Limitations and Scalability. - Zhuoyan Xu; Zhenmei Shi; Yingyu Liang (CoRR, 2024)

Fast John Ellipsoid Computation with Differential Privacy Optimization. - Jiuxiang Gu; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Junwei Yu (CoRR, 2024)

A Tighter Complexity Analysis of SparseGPT. - Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2024)

Multi-Layer Transformers Gradient Can be Approximated in Almost Linear Time. - Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (CoRR, 2024)

Discovering the Gems in Early Layers: Accelerating Long-Context LLMs with 1000x Input Token Reduction. - Zhenmei Shi; Yifei Ming; Xuan-Phi Nguyen; Yingyu Liang; Shafiq Joty (CoRR, 2024)

Fine-grained Attention I/O Complexity: Comprehensive Analysis for Backward Passes. - Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (CoRR, 2024)

Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study. - Yekun Ke; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2024)

Circuit Complexity Bounds for RoPE-based Transformer Architecture. - Bo Chen 029; Xiaoyu Li 001; Yingyu Liang; Jiangxuan Long 001; Zhenmei Shi; Zhao Song 002 (CoRR, 2024)

On the Expressive Power of Modern Hopfield Networks. - Xiaoyu Li 001; Yuanpeng Li 007; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2024)

Fast Gradient Computation for RoPE Attention in Almost Linear Time. - Yifang Chen 003; Jiayan Huo; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2024)

Theoretical Constraints on the Expressive Power of RoPE-based Tensor Attention Transformers. - Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Mingda Wan (CoRR, 2024)

Bypassing the Exponential Dependency: Looped Transformers Efficiently Learn In-context by Multi-step Gradient Descent. - Bo Chen 029; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (AISTATS, 2025)

When Can We Solve the Weighted Low Rank Approximation Problem in Truly Subquadratic Time? - Chenyang Li; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (AISTATS, 2025)

Fourier Circuits in Neural Networks and Transformers: A Case Study of Modular Arithmetic with Multiple Inputs. - Chenyang Li; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Tianyi Zhou 011 (AISTATS, 2025)

Looped ReLU MLPs May Be All You Need as Practical Programmable Computers. - Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (AISTATS, 2025)

The Computational Limits of State-Space Models and Mamba via the Lens of Circuit Complexity. - Yifang Chen 003; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CPAL, 2025)

HSR-Enhanced Sparse Attention Acceleration. - Bo Chen 029; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CPAL, 2025)

Curse of Attention: A Kernel-Based Perspective for Why Transformers Fail to Generalize on Time Series Forecasting and Beyond. - Yekun Ke; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Chiwun Yang (CPAL, 2025)

Fast John Ellipsoid Computation with Differential Privacy Optimization. - Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Junwei Yu (CPAL, 2025)

Beyond Linear Approximations: A Novel Pruning Approach for Attention Matrix. - Yingyu Liang; Jiangxuan Long 001; Zhenmei Shi; Zhao Song 002; Yufa Zhou 001 (ICLR, 2025)

NRFlow: Towards Noise-Robust Generative Modeling via High-Order Mechanism. - Bo Chen 029; Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Mingda Wan; Xugang Ye (UAI, 2025)

Differential Privacy Mechanisms in Neural Tangent Kernel Regression. - Jiuxiang Gu; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (WACV, 2025)

Circuit Complexity Bounds for Visual Autoregressive Model. - Yekun Ke; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

On Computational Limits and Provably Efficient Criteria of Visual Autoregressive Models: A Fine-Grained Complexity Analysis. - Yekun Ke; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

On the Computational Capability of Graph Neural Networks: A Circuit Complexity Bound Perspective. - Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Wei Wang; Jiahao Zhang (CoRR, 2025)

RichSpace: Enriching Text-to-Video Prompt Space via Text Embedding Interpolation. - Yuefan Cao; Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Neural Algorithmic Reasoning for Hypergraphs with Looped Transformers. - Xiaoyu Li 001; Yingyu Liang; Jiangxuan Long 001; Zhenmei Shi; Zhao Song 002; Zhen Zhuang (CoRR, 2025)

High-Order Matching for One-Step Shortcut Diffusion Models. - Bo Chen 029; Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Mingda Wan (CoRR, 2025)

Dissecting Submission Limit in Desk-Rejections: A Mathematical Analysis of Fairness in AI Conference Policies. - Yuefan Cao; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Jiahao Zhang (CoRR, 2025)

DPBloomfilter: Securing Bloom Filters with Differential Privacy. - Yekun Ke; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Universal Approximation of Visual Autoregressive Transformers. - Yifang Chen 003; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling. - Yang Cao 020; Bo Chen 029; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Mingda Wan (CoRR, 2025)

On Computational Limits of FlowAR Models: Expressivity and Efficiency. - Chengyue Gong; Yekun Ke; Xiaoyu Li 001; Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Scaling Law Phenomena Across Regression Paradigms: Multiple and Kernel Approaches. - Yifang Chen 003; Xuyang Guo; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Text-to-Image Diffusion Models Cannot Count, and Prompt Refinement Cannot Help. - Yuefan Cao; Xuyang Guo; Jiayan Huo; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Jiahao Zhang; Zhen Zhuang (CoRR, 2025)

HOFAR: High-Order Augmentation of Flow Autoregressive Transformers. - Yingyu Liang; Zhizhou Sha; Zhenmei Shi; Zhao Song 002; Mingda Wan (CoRR, 2025)

Theoretical Guarantees for High Order Trajectory Refinement in Generative Flows. - Chengyue Gong; Xiaoyu Li 001; Yingyu Liang; Jiangxuan Long 001; Zhenmei Shi; Zhao Song 002; Yu Tian (CoRR, 2025)

Time and Memory Trade-off of KV-Cache Compression in Tensor Transformer Decoding. - Yifang Chen 003; Xiaoyu Li 001; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Yu Tian (CoRR, 2025)

Exploring the Limits of KV Cache Compression in Visual Autoregressive Transformers. - Bo Chen 029; Xiaoyu Li 001; Yekun Ke; Yingyu Liang; Zhenmei Shi; Zhao Song 002 (CoRR, 2025)

Can You Count to Nine? A Human Evaluation Benchmark for Counting Limits in Modern Text-to-Video Models. - Xuyang Guo; Zekai Huang; Jiayan Huo; Yingyu Liang; Zhenmei Shi; Zhao Song 002; Jiahao Zhang (CoRR, 2025)

Provable Failure of Language Models in Learning Majority Boolean Logic via Gradient Descent. - Bo Chen 029; Zhenmei Shi; Zhao Song 002; Jiahao Zhang (CoRR, 2025)

T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation. - Xuyang Guo; Jiayan Huo; Zhenmei Shi; Zhao Song 002; Jiahao Zhang; Jiale Zhao (CoRR, 2025)

T2VTextBench: A Human Evaluation Benchmark for Textual Control in Video Generation Models. - Xuyang Guo; Jiayan Huo; Zhenmei Shi; Zhao Song 002; Jiahao Zhang; Jiale Zhao (CoRR, 2025)

T2VWorldBench: A Benchmark for Evaluating World Knowledge in Text-to-Video Generation. - Yubin Chen; Xuyang Guo; Zhenmei Shi; Zhao Song 002; Jiahao Zhang (CoRR, 2025)