THU and ICRC at TRECVID 2008. - Yingyu Liang; Xiaobing Liu; Zhikun Wang; Jianmin Li 001; Binbin Cao; Zhichao Cao 001; Zhenlong Dai; Zhishan Guo; Wen Li; Leigang Luo; Zhaoshi Meng; Yinfeng Qin; et al. (TRECVID, 2008)

Vocabulary-based hashing for image search. - Yingyu Liang; Jianmin Li 001; Bo Zhang 010 (ACM Multimedia, 2009)

THU-IMG at TRECVID 2009. - Yingyu Liang; Binbin Cao; Jianmin Li 001; Chenguang Zhu; Yongchao Zhang; Chenhao Tan; Ge Chen; Chen Sun; Jinhui Yuan; Mingxing Xu; Bo Zhang 010 (TRECVID, 2009)

Learning Vocabulary-Based Hashing with AdaBoost. - Yingyu Liang; Jianmin Li 001; Bo Zhang 010 (MMM, 2010)

Efficient Semi-supervised and Active Learning of Disjunctions. - Nina Balcan; Christopher Berlind; Steven Ehrlich; Yingyu Liang (ICML (1), 2013)

Distributed k-means and k-median clustering on general communication topologies. - Maria-Florina Balcan; Steven Ehrlich; Yingyu Liang (NIPS, 2013)

Modeling and Detecting Community Hierarchies. - Maria-Florina Balcan; Yingyu Liang (SIMBAD, 2013)

Distributed Clustering on Graphs. - Maria-Florina Balcan; Steven Ehrlich; Yingyu Liang (CoRR, 2013)

Continuous-Time Influence Maximization for Multiple Items. - Nan Du 002; Yingyu Liang; Maria-Florina Balcan; Le Song (CoRR, 2013)

Influence Function Learning in Information Diffusion Networks. - Nan Du 002; Yingyu Liang; Maria-Florina Balcan; Le Song (ICML, 2014)

Scalable Kernel Methods via Doubly Stochastic Gradients. - Bo Dai 001; Bo Xie 002; Niao He; Yingyu Liang; Anant Raj; Maria-Florina Balcan; Le Song (NIPS, 2014)

Learning Time-Varying Coverage Functions. - Nan Du 002; Yingyu Liang; Maria-Florina Balcan; Le Song (NIPS, 2014)

Improved Distributed Principal Component Analysis. - Yingyu Liang; Maria-Florina Balcan; Vandana Kanchanapally; David P. Woodruff (NIPS, 2014)

Distributed Frank-Wolfe Algorithm: A Unified Framework for Communication-Efficient Sparse Learning. - Aurélien Bellet; Yingyu Liang; Alireza Bagheri Garakani; Maria-Florina Balcan; Fei Sha (CoRR, 2014)

Robust hierarchical clustering. - Maria-Florina Balcan; Yingyu Liang; Pramod Gupta (J. Mach. Learn. Res., 2014)

Modern aspects of unsupervised learning. - Yingyu Liang (2014)

Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients. - Bo Xie 002; Yingyu Liang; Le Song (NIPS, 2015)

A Distributed Frank-Wolfe Algorithm for Communication-Efficient Sparse Learning. - Aurélien Bellet; Yingyu Liang; Alireza Bagheri Garakani; Maria-Florina Balcan; Fei Sha (SDM, 2015)

Random Walks on Context Spaces: Towards an Explanation of the Mysteries of Semantic Word Embeddings. - Sanjeev Arora; Yuanzhi Li; Yingyu Liang; Tengyu Ma 001; Andrej Risteski (CoRR, 2015)

Why are deep nets reversible: A simple theory, with implications for training. - Sanjeev Arora; Yingyu Liang; Tengyu Ma 001 (CoRR, 2015)

Distributed Kernel Principal Component Analysis. - Maria-Florina Balcan; Yingyu Liang; Le Song; David P. Woodruff; Bo Xie 002 (CoRR, 2015)

Learning in indefinite proximity spaces - recent trends. - Frank-Michael Schleif; Peter Tiño; Yingyu Liang (ESANN, 2016)

Recovery guarantee of weighted low-rank approximation via alternating minimization. - Yuanzhi Li; Yingyu Liang; Andrej Risteski (ICML, 2016)

Communication Efficient Distributed Kernel Principal Component Analysis. - Maria-Florina Balcan; Yingyu Liang; Le Song; David P. Woodruff; Bo Xie 002 (KDD, 2016)

Recovery Guarantee of Non-negative Matrix Factorization via Alternating Updates. - Yuanzhi Li; Yingyu Liang; Andrej Risteski (NIPS, 2016)

Diversity Leads to Generalization in Neural Networks. - Bo Xie 002; Yingyu Liang; Le Song (CoRR, 2016)

Mapping Between Natural Movie fMRI Responses and Word-Sequence Representations. - Kiran Vodrahalli; Po-Hsuan Chen; Yingyu Liang; Janice Chen; Esther Yong; Christopher J. Honey; Peter J. Ramadge; Kenneth A. Norman; Sanjeev Arora (CoRR, 2016)

Clustering under Perturbation Resilience. - Maria-Florina Balcan; Yingyu Liang (SIAM J. Comput., 2016)

A Latent Variable Model Approach to PMI-based Word Embeddings. - Sanjeev Arora; Yuanzhi Li; Yingyu Liang; Tengyu Ma 001; Andrej Risteski (Trans. Assoc. Comput. Linguistics, 2016)

Diverse Neural Network Learns True Target Functions. - Bo Xie 002; Yingyu Liang; Le Song (AISTATS, 2017)

A Simple but Tough-to-Beat Baseline for Sentence Embeddings. - Sanjeev Arora; Yingyu Liang; Tengyu Ma 001 (ICLR (Poster), 2017)

Generalization and Equilibrium in Generative Adversarial Nets (GANs). - Sanjeev Arora; Rong Ge 001; Yingyu Liang; Tengyu Ma 001; Yi Zhang 074 (ICML, 2017)

Differentially Private Clustering in High-Dimensional Euclidean Spaces. - Maria-Florina Balcan; Travis Dick; Yingyu Liang; Wenlong Mou; Hongyang Zhang 001 (ICML, 2017)

Provable Alternating Gradient Descent for Non-negative Matrix Factorization with Strong Correlations. - Yuanzhi Li; Yingyu Liang (ICML, 2017)

Optimal Sample Complexity for Matrix Completion and Related Problems via 𝓁s2-Regularization. - Maria-Florina Balcan; Yingyu Liang; David P. Woodruff; Hongyang Zhang 001 (CoRR, 2017)

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks. - Nan Du 002; Yingyu Liang; Maria-Florina Balcan; Manuel Gomez-Rodriguez; Hongyuan Zha; Le Song (J. Mach. Learn. Res., 2017)

Domain Adapted Word Embeddings for Improved Sentiment Classification. - Prathusha Kameswara Sarma; Yingyu Liang; Bill Sethares (DeepLo@ACL, 2018)

A La Carte Embedding: Cheap but Effective Induction of Semantic Feature Vectors. - Mikhail Khodak; Nikunj Saunshi; Yingyu Liang; Tengyu Ma 001; Brandon Stewart; Sanjeev Arora (ACL (1), 2018)

Learning Mixtures of Linear Regressions with Nearly Optimal Complexity. - Yuanzhi Li; Yingyu Liang (COLT, 2018)

Generalizing Word Embeddings using Bag of Subwords. - Jinman Zhao; Sidharth Mudgal; Yingyu Liang (EMNLP, 2018)

Matrix Completion and Related Problems via Strong Duality. - Maria-Florina Balcan; Yingyu Liang; David P. Woodruff; Hongyang Zhang 001 (ITCS, 2018)

Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data. - Yuanzhi Li; Yingyu Liang (NeurIPS, 2018)

Improving Adversarial Robustness by Data-Specific Discretization. - Jiefeng Chen 001; Xi Wu 001; Yingyu Liang; Somesh Jha (CoRR, 2018)

N-Gram Graph, A Novel Molecule Representation. - Shengchao Liu; Thevaa Chandereng; Yingyu Liang (CoRR, 2018)

Recovery Guarantees for Quadratic Tensors with Limited Observations. - Hongyang Zhang 005; Vatsal Sharan; Moses Charikar; Yingyu Liang (CoRR, 2018)

Mapping between fMRI responses to movies and their natural language annotations. - Kiran Vodrahalli; Po-Hsuan Chen; Yingyu Liang; Christopher Baldassano; Janice Chen; Esther Yong; Christopher J. Honey; Uri Hasson; Peter J. Ramadge; Kenneth A. Norman; Sanjeev Arora (NeuroImage, 2018)

Linear Algebraic Structure of Word Senses, with Applications to Polysemy. - Sanjeev Arora; Yuanzhi Li; Yingyu Liang; Tengyu Ma 001; Andrej Risteski (Trans. Assoc. Comput. Linguistics, 2018)

Loss-Balanced Task Weighting to Reduce Negative Transfer in Multi-Task Learning. - Shengchao Liu; Yingyu Liang; Anthony Gitter (AAAI, 2019)

Recovery Guarantees For Quadratic Tensors With Sparse Observations. - Hongyang Zhang 005; Vatsal Sharan; Moses Charikar; Yingyu Liang (AISTATS, 2019)

Shallow Domain Adaptive Embeddings for Sentiment Analysis. - Prathusha Kameswara Sarma; Yingyu Liang; William A. Sethares (EMNLP/IJCNLP (1), 2019)

Towards Understanding Limitations of Pixel Discretization Against Adversarial Attacks. - Jiefeng Chen 001; Xi Wu 001; Vaibhav Rastogi; Yingyu Liang; Somesh Jha (EuroS&P, 2019)

Learning and Generalization in Overparameterized Neural Networks, Going Beyond Two Layers. - Zeyuan Allen-Zhu; Yuanzhi Li; Yingyu Liang (NeurIPS, 2019)

Robust Attribution Regularization. - Jiefeng Chen 001; Xi Wu 001; Vaibhav Rastogi; Yingyu Liang; Somesh Jha (NeurIPS, 2019)

N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules. - Shengchao Liu; Mehmet Furkan Demirel; Yingyu Liang (NeurIPS, 2019)

Non-Convex Matrix Completion and Related Problems via Strong Duality. - Maria-Florina Balcan; Yingyu Liang; Zhao Song 002; David P. Woodruff; Hongyang Zhang 001 (J. Mach. Learn. Res., 2019)

Learning Relationships between Text, Audio, and Video via Deep Canonical Correlation for Multimodal Language Analysis. - Zhongkai Sun; Prathusha Kameswara Sarma; William A. Sethares; Yingyu Liang (AAAI, 2020)

Sketching Transformed Matrices with Applications to Natural Language Processing. - Yingyu Liang; Zhao Song 002; Mengdi Wang; Lin Yang 011; Xin Yang 017 (AISTATS, 2020)

Learning Entangled Single-Sample Distributions via Iterative Trimming. - Hui Yuan 002; Yingyu Liang (AISTATS, 2020)

Can Adversarial Weight Perturbations Inject Neural Backdoors. - Siddhant Garg; Adarsh Kumar 001; Vibhor Goel; Yingyu Liang (CIKM, 2020)

Learning Entangled Single-Sample Gaussians in the Subset-of-Signals Model. - Yingyu Liang; Hui Yuan 002 (COLT, 2020)

PBoS: Probabilistic Bag-of-Subwords for Generalizing Word Embedding. - Jinman Zhao; Shawn Zhong; Xiaomin Zhang; Yingyu Liang (EMNLP (Findings), 2020)

Gradients as Features for Deep Representation Learning. - Fangzhou Mu; Yingyu Liang; Yin Li 003 (ICLR, 2020)

Beyond Fine-tuning: Few-Sample Sentence Embedding Transfer. - Siddhant Garg; Rohit Kumar Sharma; Yingyu Liang (AACL/IJCNLP, 2020)

Functional Regularization for Representation Learning: A Unified Theoretical Perspective. - Siddhant Garg; Yingyu Liang (NeurIPS, 2020)

Robust Out-of-distribution Detection in Neural Networks. - Jiefeng Chen 001; Yixuan Li 001; Xi Wu 001; Yingyu Liang; Somesh Jha (CoRR, 2020)

SimpleTran: Transferring Pre-Trained Sentence Embeddings for Low Resource Text Classification. - Siddhant Garg; Rohit Kumar Sharma; Yingyu Liang (CoRR, 2020)

Representation Bayesian Risk Decompositions and Multi-Source Domain Adaptation. - Xi Wu 001; Yang Guo; Jiefeng Chen 001; Yingyu Liang; Somesh Jha; Prasad Chalasani (CoRR, 2020)

Robust Out-of-distribution Detection via Informative Outlier Mining. - Jiefeng Chen 001; Yixuan Li 001; Xi Wu 001; Yingyu Liang; Somesh Jha (CoRR, 2020)

A New View of Multi-modal Language Analysis: Audio and Video Features as Text "Styles". - Zhongkai Sun; Prathusha Kameswara Sarma; Yingyu Liang; William A. Sethares (EACL, 2021)

Detecting Errors and Estimating Accuracy on Unlabeled Data with Self-training Ensembles. - Jiefeng Chen 001; Frederick Liu; Besim Avci; Xi Wu 001; Yingyu Liang; Somesh Jha (NeurIPS, 2021)

ATOM: Robustifying Out-of-Distribution Detection Using Outlier Mining. - Jiefeng Chen 001; Yixuan Li 001; Xi Wu 001; Yingyu Liang; Somesh Jha (ECML/PKDD (3), 2021)

Towards Adversarial Robustness via Transductive Learning. - Jiefeng Chen 001; Yang Guo; Xi Wu 001; Tianqi Li; Qicheng Lao; Yingyu Liang; Somesh Jha (CoRR, 2021)

An Analysis of Attentive Walk-Aggregating Graph Neural Networks. - Mehmet Furkan Demirel; Shengchao Liu; Siddhant Garg; Yingyu Liang (CoRR, 2021)

Multi-Scale Anti-Occlusion Correlation Filters Object Tracking Method Based on Complementary Features. - Xiuhua Hu; Yuan Chen; Yan Hui; Yingyu Liang; Guiping Li; Changyuan Wang (Int. J. Pattern Recognit. Artif. Intell., 2021)

Adaptive Mho Characteristic-Based Distance Protection for Lines Emanating From Photovoltaic Power Plants Under Unbalanced Faults. - Yingyu Liang; Wulin Li; Wenting Zha (IEEE Syst. J., 2021)

Towards Evaluating the Robustness of Neural Networks Learned by Transduction. - Jiefeng Chen 001; Xi Wu 001; Yang Guo; Yingyu Liang; Somesh Jha (ICLR, 2022)

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)

On the identifiability of mixtures of ranking models. - Xiaomin Zhang; Xucheng Zhang; Po-Ling Loh; Yingyu Liang (CoRR, 2022)

Siamese Network Object Tracking Algorithm Combining Attention Mechanism and Correlation Filter Theory. - Xiuhua Hu; Huan Liu; Yuan Chen; Yan Hui; Yingyu Liang; Xi Wu 001 (Int. J. Pattern Recognit. Artif. Intell., 2022)

Person Re-Identification Method Based on the Construction of Graph Convolutional Network with Attribute Feature. - Xiuhua Hu; Yingyu Liang; Yan Hui; Xi Wu 001; Huan Liu; Xuyang Hu (Int. J. Pattern Recognit. Artif. Intell., 2022)

Person Re-Identification Combined with Style Transfer and Pose Generation. - Yan Hui; Yingyu Liang; Xiuhua Hu; Xi Wu 001; Huan Liu (Int. J. Pattern Recognit. Artif. Intell., 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)

Stratified Adversarial Robustness with Rejection. - Jiefeng Chen 001; Jayaram Raghuram; Jihye Choi; Xi Wu 001; Yingyu Liang; Somesh Jha (ICML, 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)

What Knowledge Gets Distilled in Knowledge Distillation? - Utkarsh Ojha; Yuheng Li; Anirudh Sundara Rajan; Yingyu Liang; Yong Jae Lee (NeurIPS, 2023)

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

Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection. - Nils Palumbo; Yang Guo; Xi Wu 001; Jiefeng Chen 001; Yingyu Liang; Somesh Jha (CoRR, 2023)

Pilot Protection Based on Two-Dimensional Space Projection of Dual Differential Currents for Lines Connecting MMC-HVDC Stations. - Yingyu Liang; Yi Ren; Zhi Zhang (IEEE Trans. Ind. Electron., 2023)

An Enhanced Current Differential Protection for AC Transmission Lines Connecting MMC-HVDC Stations. - Yingyu Liang; Yi Ren; Weixuan He (IEEE Syst. J., 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)

Two Heads are Actually Better than One: Towards Better Adversarial Robustness via Transduction and Rejection. - Nils Palumbo; Yang Guo; Xi Wu 001; Jiefeng Chen 001; Yingyu Liang; Somesh Jha (ICML, 2024)

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

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)

Learning to Inference Adaptively for Multimodal Large Language Models. - Zhuoyan Xu; Khoi Duc Nguyen; Preeti Mukherjee; Saurabh Bagchi; Somali Chaterji; Yingyu Liang; Yin Li 003 (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)

Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds. - Yang Guo; Yutian Tao 001; Yifei Ming; Robert D. Nowak; Yingyu Liang (CoRR, 2025)