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2020 – today
- 2025
[c22]Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, Junda Wu, Xintong Li, Ryan Aponte, Hanjia Lyu, Joe Barrow, Hongjie Chen, Franck Dernoncourt, Branislav Kveton, Tong Yu, Ruiyi Zhang, Jiuxiang Gu, Nesreen K. Ahmed, Yu Wang, Xiang Chen, Hanieh Deilamsalehy, Sungchul Kim, Zhengmian Hu, Yue Zhao, Nedim Lipka, Seunghyun Yoon, Ting-Hao Kenneth Huang, Zichao Wang, Puneet Mathur, Soumyabrata Pal, Koyel Mukherjee, Zhehao Zhang, Namyong Park, Thien Huu Nguyen, Jiebo Luo, Ryan A. Rossi, Julian J. McAuley:
From Selection to Generation: A Survey of LLM-based Active Learning. ACL (1) 2025: 14552-14569- [c21]Dang Nguyen, Jian Chen, Yu Wang, Gang Wu, Namyong Park, Zhengmian Hu, Hanjia Lyu, Junda Wu, Ryan Aponte, Yu Xia, Xintong Li, Jing Shi, Hongjie Chen, Viet Dac Lai, Zhouhang Xie, Sungchul Kim, Ruiyi Zhang, Tong Yu, Md. Mehrab Tanjim, Nesreen K. Ahmed, Puneet Mathur, Seunghyun Yoon, Lina Yao, Branislav Kveton, Jihyung Kil, Thien Huu Nguyen, Trung Bui, Tianyi Zhou, Ryan A. Rossi, Franck Dernoncourt:
GUI Agents: A Survey. ACL (Findings) 2025: 22522-22538 - [c20]Yizhou Wang, Lingzhi Zhang, Yue Bai, Mang Tik Chiu, Zhengmian Hu, Mingyuan Zhang, Qihua Dong, Yu Yin, Sohrab Amirghodsi, Yun Fu:
Cautious Next Token Prediction. ACL (Findings) 2025: 25685-25697 - [c19]Zhengmian Hu, Tong Zheng, Vignesh Viswanathan, Ziyi Chen, Ryan A. Rossi, Yihan Wu, Dinesh Manocha, Heng Huang:
Towards Optimal Multi-draft Speculative Decoding. ICLR 2025 - [i26]Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, Junda Wu, Xintong Li
, Ryan Aponte, Hanjia Lyu, Joe Barrow, Hongjie Chen, Franck Dernoncourt, Branislav Kveton, Tong Yu, Ruiyi Zhang, Jiuxiang Gu, Nesreen K. Ahmed, Yu Wang, Xiang Chen, Hanieh Deilamsalehy, Sungchul Kim, Zhengmian Hu, Yue Zhao, Nedim Lipka, Seunghyun Yoon, Ting-Hao Kenneth Huang, Zichao Wang, Puneet Mathur, Soumyabrata Pal, Koyel Mukherjee, Zhehao Zhang, Namyong Park, Thien Huu Nguyen, Jiebo Luo, Ryan A. Rossi, Julian J. McAuley:
From Selection to Generation: A Survey of LLM-based Active Learning. CoRR abs/2502.11767 (2025) - [i25]Zhengmian Hu, Tong Zheng, Vignesh Viswanathan, Ziyi Chen, Ryan A. Rossi, Yihan Wu, Dinesh Manocha, Heng Huang:
Towards Optimal Multi-draft Speculative Decoding. CoRR abs/2502.18779 (2025) - [i24]Md. Mehrab Tanjim, Ryan A. Rossi, Mike Rimer, Xiang Chen, Sungchul Kim, Vaishnavi Muppala, Tong Yu, Zhengmian Hu, Ritwik Sinha, Wei Zhang, Iftikhar Ahamath Burhanuddin, Franck Dernoncourt:
Exploring Rewriting Approaches for Different Conversational Tasks. CoRR abs/2502.18860 (2025) - [i23]Li Li, Peilin Cai, Ryan A. Rossi, Franck Dernoncourt, Branislav Kveton, Junda Wu, Tong Yu, Linxin Song, Tiankai Yang, Yuehan Qin, Nesreen K. Ahmed, Samyadeep Basu, Subhojyoti Mukherjee, Ruiyi Zhang, Zhengmian Hu, Bo Ni, Yuxiao Zhou, Zichao Wang, Yue Huang, Yu Wang, Xiangliang Zhang, Philip S. Yu, Xiyang Hu, Yue Zhao:
A Personalized Conversational Benchmark: Towards Simulating Personalized Conversations. CoRR abs/2505.14106 (2025) - [i22]Yizhou Wang, Lingzhi Zhang, Yue Bai, Mang Tik Chiu, Zhengmian Hu, Mingyuan Zhang, Qihua Dong, Yu Yin, Sohrab Amirghodsi, Yun Fu:
Cautious Next Token Prediction. CoRR abs/2507.03038 (2025) - [i21]Junda Wu, Yuxin Xiong, Xintong Li, Zhengmian Hu, Tong Yu, Rui Wang, Xiang Chen, Jingbo Shang, Julian J. McAuley:
CTRLS: Chain-of-Thought Reasoning via Latent State-Transition. CoRR abs/2507.08182 (2025) - [i20]Yueqian Lin, Zhengmian Hu, Qinsi Wang, Yudong Liu, Hengfan Zhang, Jayakumar Subramanian, Nikos Vlassis, Hai Helen Li, Yiran Chen:
Voice Evaluation of Reasoning Ability: Diagnosing the Modality-Induced Performance Gap. CoRR abs/2509.26542 (2025) - [i19]Yueqian Lin, Zhengmian Hu, Jayakumar Subramanian, Qinsi Wang, Nikos Vlassis, Hai Helen Li, Yiran Chen:
AsyncVoice Agent: Real-Time Explanation for LLM Planning and Reasoning. CoRR abs/2510.16156 (2025) - 2024
- [b1]Zhengmian Hu:
Understanding and Enhancing Machine Learning Models with Theoretical Foundations. University of Maryland, College Park, MD, USA, 2024 - [c18]Zhengmian Hu, Tong Zheng, Heng Huang:
A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution. EMNLP 2024: 13216-13227 - [c17]Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang:
Unbiased Watermark for Large Language Models. ICLR 2024 - [c16]Zhengmian Hu, Heng Huang:
Accelerated Speculative Sampling Based on Tree Monte Carlo. ICML 2024 - [c15]Yihan Wu, Zhengmian Hu, Junfeng Guo, Hongyang Zhang, Heng Huang:
A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models. ICML 2024 - [c14]Ziyi Chen, Yan Wen, Zhengmian Hu, Heng Huang:
Robust Reinforcement Learning with General Utility. NeurIPS 2024 - [c13]Zhengmian Hu, Heng Huang:
Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models. NeurIPS 2024 - [i18]Yihan Wu, Ruibo Chen, Zhengmian Hu, Yanshuo Chen, Junfeng Guo, Hongyang Zhang, Heng Huang:
Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions. CoRR abs/2406.02603 (2024) - [i17]Chien Van Nguyen, Xuan Shen, Ryan Aponte, Yu Xia, Samyadeep Basu, Zhengmian Hu, Jian Chen, Mihir Parmar, Sasidhar Kunapuli, Joe Barrow, Junda Wu, Ashish Singh, Yu Wang, Jiuxiang Gu, Franck Dernoncourt, Nesreen K. Ahmed, Nedim Lipka, Ruiyi Zhang, Xiang Chen, Tong Yu, Sungchul Kim, Hanieh Deilamsalehy, Namyong Park, Mike Rimer, Zhehao Zhang, Huanrui Yang, Ryan A. Rossi, Thien Huu Nguyen:
A Survey of Small Language Models. CoRR abs/2410.20011 (2024) - [i16]Zhengmian Hu, Heng Huang:
Inevitable Trade-off between Watermark Strength and Speculative Sampling Efficiency for Language Models. CoRR abs/2410.20418 (2024) - [i15]Zhengmian Hu, Tong Zheng, Heng Huang:
A Bayesian Approach to Harnessing the Power of LLMs in Authorship Attribution. CoRR abs/2410.21716 (2024) - [i14]Yanshuo Chen, Zhengmian Hu, Wei Chen, Heng Huang:
Fast and scalable Wasserstein-1 neural optimal transport solver for single-cell perturbation prediction. CoRR abs/2411.00614 (2024) - [i13]Junda Wu, Hanjia Lyu, Yu Xia, Zhehao Zhang, Joe Barrow, Ishita Kumar, Mehrnoosh Mirtaheri, Hongjie Chen, Ryan A. Rossi, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, Jiuxiang Gu, Nesreen K. Ahmed, Yu Wang, Xiang Chen, Hanieh Deilamsalehy, Namyong Park, Sungchul Kim, Huanrui Yang, Subrata Mitra, Zhengmian Hu, Nedim Lipka, Dang Nguyen, Yue Zhao, Jiebo Luo, Julian J. McAuley:
Personalized Multimodal Large Language Models: A Survey. CoRR abs/2412.02142 (2024) - [i12]Dang Nguyen, Jian Chen, Yu Wang, Gang Wu, Namyong Park, Zhengmian Hu, Hanjia Lyu, Junda Wu, Ryan Aponte, Yu Xia, Xintong Li, Jing Shi, Hongjie Chen, Viet Dac Lai, Zhouhang Xie, Sungchul Kim, Ruiyi Zhang, Tong Yu, Md. Mehrab Tanjim, Nesreen K. Ahmed, Puneet Mathur, Seunghyun Yoon, Lina Yao, Branislav Kveton, Thien Huu Nguyen, Trung Bui, Tianyi Zhou, Ryan A. Rossi, Franck Dernoncourt:
GUI Agents: A Survey. CoRR abs/2412.13501 (2024) - 2023
- [c12]Xidong Wu, Zhengmian Hu, Heng Huang:
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems. AAAI 2023: 10370-10378 - [c11]Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang:
Faster Adaptive Federated Learning. AAAI 2023: 10379-10387 - [c10]Feihu Huang, Xidong Wu, Zhengmian Hu:
AdaGDA: Faster Adaptive Gradient Descent Ascent Methods for Minimax Optimization. AISTATS 2023: 2365-2389 - [c9]Zhengmian Hu, Heng Huang:
Tighter Analysis for ProxSkip. ICML 2023: 13469-13496 - [c8]Zhengmian Hu, Xidong Wu, Heng Huang:
Beyond Lipschitz Smoothness: A Tighter Analysis for Nonconvex Optimization. ICML 2023: 13652-13678 - [c7]Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang:
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. KDD 2023: 2648-2659 - [c6]Zhengmian Hu, Heng Huang:
Optimization and Bayes: A Trade-off for Overparameterized Neural Networks. NeurIPS 2023 - [c5]Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang:
Federated Conditional Stochastic Optimization. NeurIPS 2023 - [c4]Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang:
Solving a Class of Non-Convex Minimax Optimization in Federated Learning. NeurIPS 2023 - [i11]Xidong Wu, Zhengmian Hu, Heng Huang:
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems. CoRR abs/2302.03825 (2023) - [i10]Xidong Wu, Zhengmian Hu, Jian Pei, Heng Huang:
Serverless Federated AUPRC Optimization for Multi-Party Collaborative Imbalanced Data Mining. CoRR abs/2308.03035 (2023) - [i9]Xidong Wu, Jianhui Sun, Zhengmian Hu, Junyi Li, Aidong Zhang, Heng Huang:
Federated Conditional Stochastic Optimization. CoRR abs/2310.02524 (2023) - [i8]Xidong Wu, Jianhui Sun, Zhengmian Hu, Aidong Zhang, Heng Huang:
Solving a Class of Non-Convex Minimax Optimization in Federated Learning. CoRR abs/2310.03613 (2023) - [i7]Yihan Wu, Zhengmian Hu, Hongyang Zhang, Heng Huang:
DiPmark: A Stealthy, Efficient and Resilient Watermark for Large Language Models. CoRR abs/2310.07710 (2023) - [i6]Zhengmian Hu, Lichang Chen, Xidong Wu, Yihan Wu, Hongyang Zhang, Heng Huang:
Unbiased Watermark for Large Language Models. CoRR abs/2310.10669 (2023) - [i5]Ruibo Chen, Tianyi Xiong, Yihan Wu, Guodong Liu, Zhengmian Hu, Lichang Chen, Yanshuo Chen, Chenxi Liu, Heng Huang:
GPT-4 Vision on Medical Image Classification - A Case Study on COVID-19 Dataset. CoRR abs/2310.18498 (2023) - [i4]Zhengmian Hu, Gang Wu, Saayan Mitra, Ruiyi Zhang, Tong Sun, Heng Huang, Vishy Swaminathan:
Token-Level Adversarial Prompt Detection Based on Perplexity Measures and Contextual Information. CoRR abs/2311.11509 (2023) - 2022
- [i3]Xidong Wu, Feihu Huang, Zhengmian Hu, Heng Huang:
Faster Adaptive Federated Learning. CoRR abs/2212.00974 (2022) - 2021
- [c3]Huimin Wu, Zhengmian Hu, Bin Gu:
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. AAAI 2021: 10329-10337 - [c2]Zhengmian Hu, Heng Huang:
On the Random Conjugate Kernel and Neural Tangent Kernel. ICML 2021: 4359-4368 - [c1]Zhengmian Hu, Feihu Huang, Heng Huang:
Optimal Underdamped Langevin MCMC Method. NeurIPS 2021: 19363-19374 - [i2]Zhengmian Hu, Feihu Huang, Heng Huang:
A New Framework for Variance-Reduced Hamiltonian Monte Carlo. CoRR abs/2102.04613 (2021) - [i1]Huimin Wu, Zhengmian Hu, Bin Gu:
Fast and Scalable Adversarial Training of Kernel SVM via Doubly Stochastic Gradients. CoRR abs/2107.09937 (2021)
Coauthor Index
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