| 2024 | Pessimism Meets Risk: Risk-Sensitive Offline Reinforcement Learning. | Dake Zhang, Boxiang Lyu, Shuang Qiu, Mladen Kolar, Tong Zhang |
| 2024 | Nonparametric Teaching of Implicit Neural Representations. | Chen Zhang, Steven Tin Sui Luo, Jason Chun Lok Li, Yik-Chung Wu, Ngai Wong |
| 2024 | Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark. | Yihua Zhang, Pingzhi Li, Junyuan Hong, Jiaxiang Li, Yimeng Zhang, Wenqing Zheng, Pin-Yu Chen, Jason D. Lee, Wotao Yin, Mingyi Hong, Zhangyang Wang, Sijia Liu, Tianlong Chen |
| 2024 | An Interpretable Evaluation of Entropy-based Novelty of Generative Models. | Jingwei Zhang, Cheuk Ting Li, Farzan Farnia |
| 2024 | Wukong: Towards a Scaling Law for Large-Scale Recommendation. | Buyun Zhang, Liang Luo, Yuxin Chen, Jade Nie, Xi Liu, Shen Li, Yanli Zhao, Yuchen Hao, Yantao Yao, Ellie Dingqiao Wen, Jongsoo Park, Maxim Naumov, Wenlin Chen |
| 2024 | Deep Regression Representation Learning with Topology. | Shihao Zhang, Kenji Kawaguchi, Angela Yao |
| 2024 | Towards Causal Foundation Model: on Duality between Optimal Balancing and Attention. | Jiaqi Zhang, Joel Jennings, Agrin Hilmkil, Nick Pawlowski, Cheng Zhang, Chao Ma |
| 2024 | Advancing DRL Agents in Commercial Fighting Games: Training, Integration, and Agent-Human Alignment. | Chen Zhang, Qiang He, Yuan Zhou, Elvis S. Liu, Hong Wang, Jian Zhao, Yang Wang |
| 2024 | On the Duality Between Sharpness-Aware Minimization and Adversarial Training. | Yihao Zhang, Hangzhou He, Jingyu Zhu, Huanran Chen, Yifei Wang, Zeming Wei |
| 2024 | Generating Chain-of-Thoughts with a Pairwise-Comparison Approach to Searching for the Most Promising Intermediate Thought. | Zhen-Yu Zhang, Siwei Han, Huaxiu Yao, Gang Niu, Masashi Sugiyama |
| 2024 | Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks. | Guanhua Zhang, Moritz Hardt |
| 2024 | Model-based Reinforcement Learning for Parameterized Action Spaces. | Renhao Zhang, Haotian Fu, Yilin Miao, George Konidaris |
| 2024 | MILP-FBGen: LP/MILP Instance Generation with Feasibility/Boundedness. | Yahong Zhang, Chenchen Fan, Donghui Chen, Congrui Li, Wenli Ouyang, Mingda Zhu, Junchi Yan |
| 2024 | Watermarks in the Sand: Impossibility of Strong Watermarking for Language Models. | Hanlin Zhang, Benjamin L. Edelman, Danilo Francati, Daniele Venturi, Giuseppe Ateniese, Boaz Barak |
| 2024 | Towards Certified Unlearning for Deep Neural Networks. | Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li |
| 2024 | Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining. | Qi Zhang, Tianqi Du, Haotian Huang, Yifei Wang, Yisen Wang |
| 2024 | Reshape and Adapt for Output Quantization (RAOQ): Quantization-aware Training for In-memory Computing Systems. | Bonan Zhang, Chia-Yu Chen, Naveen Verma |
| 2024 | Verification of Machine Unlearning is Fragile. | Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li |
| 2024 | Improving Equivariant Graph Neural Networks on Large Geometric Graphs via Virtual Nodes Learning. | Yuelin Zhang, Jiacheng Cen, Jiaqi Han, Zhiqiang Zhang, Jun Zhou, Wenbing Huang |
| 2024 | Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation. | Tonghe Zhang, Yu Chen, Longbo Huang |
| 2024 | LQER: Low-Rank Quantization Error Reconstruction for LLMs. | Cheng Zhang, Jianyi Cheng, George Anthony Constantinides, Yiren Zhao |
| 2024 | Random Scaling and Momentum for Non-smooth Non-convex Optimization. | Qinzi Zhang, Ashok Cutkosky |
| 2024 | SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation. | Junjie Zhang, Chenjia Bai, Haoran He, Zhigang Wang, Bin Zhao, Xiu Li, Xuelong Li |
| 2024 | Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders. | Zhiheng Zhang |
| 2024 | GroupCover: A Secure, Efficient and Scalable Inference Framework for On-device Model Protection based on TEEs. | Zheng Zhang, Na Wang, Ziqi Zhang, Yao Zhang, Tianyi Zhang, Jianwei Liu, Ye Wu |