Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. - Huimin Wu; Zhengmian Hu; Bin Gu 001 (AAAI, 2021)

On the Random Conjugate Kernel and Neural Tangent Kernel. - Zhengmian Hu; Heng Huang (ICML, 2021)

Optimal Underdamped Langevin MCMC Method. - Zhengmian Hu; Feihu Huang 001; Heng Huang (NeurIPS, 2021)

A New Framework for Variance-Reduced Hamiltonian Monte Carlo. - Zhengmian Hu; Feihu Huang 001; Heng Huang (CoRR, 2021)

Decentralized Riemannian Algorithm for Nonconvex Minimax Problems. - Xidong Wu; Zhengmian Hu; Heng Huang (AAAI, 2023)

Faster Adaptive Federated Learning. - Xidong Wu; Feihu Huang 001; Zhengmian Hu; Heng Huang (AAAI, 2023)

AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. - Feihu Huang 001; Xidong Wu; Zhengmian Hu (AISTATS, 2023)

Tighter Analysis for ProxSkip. - Zhengmian Hu; Heng Huang (ICML, 2023)

Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization. - Zhengmian Hu; Xidong Wu; Heng Huang (ICML, 2023)

Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. - Xidong Wu; Zhengmian Hu; Jian Pei 001; Heng Huang (KDD, 2023)

Optimization and Bayes: A Trade-off for Overparameterized Neural Networks. - Zhengmian Hu; Heng Huang (NeurIPS, 2023)

Federated Conditional Stochastic Optimization. - Xidong Wu; Jianhui Sun; Zhengmian Hu; Junyi Li; Aidong Zhang; Heng Huang (NeurIPS, 2023)

Solving a Class of Non-Convex Minimax Optimization in Federated Learning. - Xidong Wu; Jianhui Sun; Zhengmian Hu; Aidong Zhang; Heng Huang (NeurIPS, 2023)

DiPmark: A Stealthy, Efficient and Resilient Watermark for Large Language Models. - Yihan Wu; Zhengmian Hu; Hongyang Zhang 001; Heng Huang (CoRR, 2023)

GPT-4 Vision on Medical Image Classification - A Case Study on COVID-19 Dataset. - Ruibo Chen; Tianyi Xiong; Yihan Wu; Guodong Liu; Zhengmian Hu; Lichang Chen; Yanshuo Chen; Chenxi Liu; Heng Huang (CoRR, 2023)

Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information. - Zhengmian Hu; Gang Wu 013; Saayan Mitra; Ruiyi Zhang 002; Tong Sun 005; Heng Huang; Vishy Swaminathan (CoRR, 2023)

A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution. - Zhengmian Hu; Tong Zheng; Heng Huang (EMNLP, 2024)

Unbiased Watermark for Large Language Models. - Zhengmian Hu; Lichang Chen; Xidong Wu; Yihan Wu; Hongyang Zhang 001; Heng Huang (ICLR, 2024)

Accelerated Speculative Sampling Based on Tree Monte Carlo. - Zhengmian Hu; Heng Huang (ICML, 2024)

A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models. - Yihan Wu; Zhengmian Hu; Junfeng Guo; Hongyang Zhang 001; Heng Huang (ICML, 2024)

Robust Reinforcement Learning with General Utility. - Ziyi Chen 002; Yan Wen; Zhengmian Hu; Heng Huang (NeurIPS, 2024)

Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models. - Zhengmian Hu; Heng Huang (NeurIPS, 2024)

Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions. - Yihan Wu; Ruibo Chen; Zhengmian Hu; Yanshuo Chen; Junfeng Guo; Hongyang Zhang 001; Heng Huang (CoRR, 2024)

A Survey of Small Language Models. - Chien Van Nguyen; Xuan Shen; Ryan Aponte; Yu Xia 007; Samyadeep Basu; Zhengmian Hu; Jian Chen 043; Mihir Parmar; Sasidhar Kunapuli; Joe Barrow; Junda Wu; Ashish Singh; et al. (CoRR, 2024)

Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction. - Yanshuo Chen; Zhengmian Hu; Wei Chen; Heng Huang (CoRR, 2024)

Personalized Multimodal Large Language Models: A Survey. - Junda Wu; Hanjia Lyu; Yu Xia 007; Zhehao Zhang 001; Joe Barrow; Ishita Kumar; Mehrnoosh Mirtaheri; Hongjie Chen 003; Ryan A. Rossi; Franck Dernoncourt; Tong Yu 001; Ruiyi Zhang 002; et al. (CoRR, 2024)

GUI Agents: A Survey. - Dang Nguyen; Jian Chen 043; Yu Wang 160; Gang Wu 013; Namyong Park; Zhengmian Hu; Hanjia Lyu; Junda Wu; Ryan Aponte; Yu Xia 007; Xintong Li 001; Jing Shi 005; et al. (CoRR, 2024)

Understanding and Enhancing Machine Learning Models with Theoretical Foundations. - Zhengmian Hu (2024)

GUI Agents: A Survey. - Dang Nguyen; Jian Chen 043; Yu Wang 160; Gang Wu 013; Namyong Park; Zhengmian Hu; Hanjia Lyu; Junda Wu; Ryan Aponte; Yu Xia 007; Xintong Li 001; Jing Shi 005; et al. (ACL (Findings), 2025)

Cautious Next Token Prediction. - Yizhou Wang 006; Lingzhi Zhang; Yue Bai; Mang Tik Chiu; Zhengmian Hu; Mingyuan Zhang; Qihua Dong; Yu Yin 001; Sohrab Amirghodsi; Yun Fu 001 (ACL (Findings), 2025)

From Selection to Generation: A Survey of LLM-based Active Learning. - Yu Xia 007; Subhojyoti Mukherjee; Zhouhang Xie; Junda Wu; Xintong Li 001; Ryan Aponte; Hanjia Lyu; Joe Barrow; Hongjie Chen 003; Franck Dernoncourt; Branislav Kveton; Tong Yu 001; et al. (ACL (1), 2025)

Towards Optimal Multi-draft Speculative Decoding. - Zhengmian Hu; Tong Zheng; Vignesh Viswanathan; Ziyi Chen 002; Ryan A. Rossi; Yihan Wu; Dinesh Manocha; Heng Huang (ICLR, 2025)

Exploring Rewriting Approaches for Different Conversational Tasks. - Md. Mehrab Tanjim; Ryan A. Rossi; Mike Rimer; Xiang Chen; Sungchul Kim; Vaishnavi Muppala; Tong Yu 001; Zhengmian Hu; Ritwik Sinha; Wei Zhang; Iftikhar Ahamath Burhanuddin; Franck Dernoncourt (CoRR, 2025)

A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations. - Li Li 006; Peilin Cai; Ryan A. Rossi; Franck Dernoncourt; Branislav Kveton; Junda Wu; Tong Yu 001; Linxin Song; Tiankai Yang 001; Yuehan Qin; Nesreen K. Ahmed; Samyadeep Basu; et al. (CoRR, 2025)

CTRLS: Chain-of-Thought Reasoning via Latent State-Transition. - Junda Wu; Yuxin Xiong; Xintong Li 001; Zhengmian Hu; Tong Yu 001; Rui Wang 088; Xiang Chen; Jingbo Shang; Julian J. McAuley (CoRR, 2025)