SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions. - Mao Ye 006; Chengyue Gong; Qiang Liu 001 (ACL, 2020)

Good Subnetworks Provably Exist: Pruning via Greedy Forward Selection. - Mao Ye 006; Chengyue Gong; Lizhen Nie; Denny Zhou; Adam R. Klivans; Qiang Liu 001 (ICML, 2020)

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. - Denny Zhou; Mao Ye 006; Chen Chen; Tianjian Meng; Mingxing Tan; Xiaodan Song; Quoc V. Le; Qiang Liu 001; Dale Schuurmans (ICML, 2020)

Stein Self-Repulsive Dynamics: Benefits From Past Samples. - Mao Ye 006; Tongzheng Ren; Qiang Liu 001 (NeurIPS, 2020)

Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough. - Mao Ye 006; Lemeng Wu; Qiang Liu 001 (NeurIPS, 2020)

Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework. - Dinghuai Zhang; Mao Ye 006; Chengyue Gong; Zhanxing Zhu; Qiang Liu 001 (NeurIPS, 2020)

MaxUp: A Simple Way to Improve Generalization of Neural Network Training. - ChengYue Gong; Tongzheng Ren; Mao Ye 006; Qiang Liu 001 (CoRR, 2020)

Steepest Descent Neural Architecture Optimization: Escaping Local Optimum with Signed Neural Splitting. - Lemeng Wu; Mao Ye 006; Qi Lei; Jason D. Lee; Qiang Liu 001 (CoRR, 2020)

Adaptive Dense-to-Sparse Paradigm for Pruning Online Recommendation System with Non-Stationary Data. - Mao Ye 006; Dhruv Choudhary; Jiecao Yu; Ellie Wen; Zeliang Chen; Jiyan Yang; Jongsoo Park; Qiang Liu 001; Arun Kejariwal (CoRR, 2020)

Post-training Quantization with Multiple Points: Mixed Precision without Mixed Precision. - Xingchao Liu; Mao Ye 006; Dengyong Zhou; Qiang Liu 001 (AAAI, 2021)

MaxUp: Lightweight Adversarial Training With Data Augmentation Improves Neural Network Training. - Chengyue Gong; Tongzheng Ren; Mao Ye 006; Qiang Liu 001 (CVPR, 2021)

VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments. - Lizhen Nie; Mao Ye 006; Qiang Liu 001; Dan Nicolae (ICLR, 2021)

argmax centroid. - Chengyue Gong; Mao Ye 006; Qiang Liu 001 (NeurIPS, 2021)

Centroid Approximation for Bootstrap. - Mao Ye 006; Qiang Liu 001 (CoRR, 2021)

Centroid Approximation for Bootstrap: Improving Particle Quality at Inference. - Mao Ye 006; Qiang Liu 001 (ICML, 2022)

BOME! Bilevel Optimization Made Easy: A Simple First-Order Approach. - Bo Liu 042; Mao Ye 006; Stephen Wright; Peter Stone 001; Qiang Liu 001 (NeurIPS, 2022)

Diffusion-based Molecule Generation with Informative Prior Bridges. - Lemeng Wu; Chengyue Gong; Xingchao Liu; Mao Ye 006; Qiang Liu 001 (NeurIPS, 2022)

First Hitting Diffusion Models for Generating Manifold, Graph and Categorical Data. - Mao Ye 006; Lemeng Wu; Qiang Liu 001 (NeurIPS, 2022)

Pareto navigation gradient descent: a first-order algorithm for optimization in pareto set. - Mao Ye 006; Qiang Liu 001 (UAI, 2022)

Future gradient descent for adapting the temporal shifting data distribution in online recommendation systems. - Mao Ye 006; Ruichen Jiang; Haoxiang Wang 003; Dhruv Choudhary; Xiaocong Du; Bhargav Bhushanam; Aryan Mokhtari; Arun Kejariwal; Qiang Liu 001 (UAI, 2022)

Let us Build Bridges: Understanding and Extending Diffusion Generative Models. - Xingchao Liu; Lemeng Wu; Mao Ye 006; Qiang Liu 001 (CoRR, 2022)

First Hitting Diffusion Models. - Mao Ye 006; Lemeng Wu; Qiang Liu 001 (CoRR, 2022)

Efficient Transformer-based 3D Object Detection with Dynamic Token Halting. - Mao Ye 006; Gregory P. Meyer; Yuning Chai; Qiang Liu 001 (ICCV, 2023)

Learning Diffusion Bridges on Constrained Domains. - Xingchao Liu; Lemeng Wu; Mao Ye 006; Qiang Liu 001 (ICLR, 2023)

Fine-Grained Gradient Restriction: A Simple Approach for Mitigating Catastrophic Forgetting. - Bo Liu 042; Mao Ye 006; Peter Stone 001; Qiang Liu 001 (CoRR, 2024)

VLMine: Long-Tail Data Mining with Vision Language Models. - Mao Ye 006; Gregory P. Meyer; Zaiwei Zhang; Dennis Park; Siva Karthik Mustikovela; Yuning Chai; Eric M. Wolff (WACV (Workshops), 2025)

Generative Data Mining with Longtail-Guided Diffusion. - David S. Hayden; Mao Ye 006; Timur Garipov; Gregory P. Meyer; Carl Vondrick; Zhao Chen; Yuning Chai; Eric M. Wolff; Siddhartha S. Srinivasa (CoRR, 2025)