| 2024 | Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach. | Weijia Zhang, Chenlong Yin, Hao Liu, Xiaofang Zhou, Hui Xiong |
| 2024 | Rethinking Guidance Information to Utilize Unlabeled Samples: A Label Encoding Perspective. | Yulong Zhang, Yuan Yao, Shuhao Chen, Pengrong Jin, Yu Zhang, Jian Jin, Jiangang Lu |
| 2024 | Exploring the Benefit of Activation Sparsity in Pre-training. | Zhengyan Zhang, Chaojun Xiao, Qiujieli Qin, Yankai Lin, Zhiyuan Zeng, Xu Han, Zhiyuan Liu, Ruobing Xie, Maosong Sun, Jie Zhou |
| 2024 | Interpreting and Improving Large Language Models in Arithmetic Calculation. | Wei Zhang, Chaoqun Wan, Yonggang Zhang, Yiu-ming Cheung, Xinmei Tian, Xu Shen, Jieping Ye |
| 2024 | Directly Denoising Diffusion Models. | Dan Zhang, Jingjing Wang, Feng Luo |
| 2024 | Matrix Information Theory for Self-Supervised Learning. | Yifan Zhang, Zhiquan Tan, Jingqin Yang, Weiran Huang, Yang Yuan |
| 2024 | Learning Low-dimensional Latent Dynamics from High-dimensional Observations: Non-asymptotics and Lower Bounds. | Yuyang Zhang, Shahriar Talebi, Na Li |
| 2024 | Switchable Decision: Dynamic Neural Generation Networks. | Shujian Zhang, Korawat Tanwisuth, Chengyue Gong, Pengcheng He, Mingyuan Zhou |
| 2024 | Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning. | Qiankun Zhang, Aocheng Shen, Boyu Zhang, Hanrui Jiang, Bingqian Du |
| 2024 | Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning. | Zongmeng Zhang, Yufeng Shi, Jinhua Zhu, Wengang Zhou, Xiang Qi, Peng Zhang, Houqiang Li |
| 2024 | Provable Representation with Efficient Planning for Partially Observable Reinforcement Learning. | Hongming Zhang, Tongzheng Ren, Chenjun Xiao, Dale Schuurmans, Bo Dai |
| 2024 | Flexible Residual Binarization for Image Super-Resolution. | Yulun Zhang, Haotong Qin, Zixiang Zhao, Xianglong Liu, Martin Danelljan, Fisher Yu |
| 2024 | Online Resource Allocation with Non-Stationary Customers. | Xiaoyue Zhang, Hanzhang Qin, Mabel C. Chou |
| 2024 | How Language Model Hallucinations Can Snowball. | Muru Zhang, Ofir Press, William Merrill, Alisa Liu, Noah A. Smith |
| 2024 | A Federated Stochastic Multi-level Compositional Minimax Algorithm for Deep AUC Maximization. | Xinwen Zhang, Ali Payani, Myungjin Lee, Richard Souvenir, Hongchang Gao |
| 2024 | Sparsest Models Elude Pruning: An Expos of Pruning's Current Capabilities. | Stephen Zhang, Vardan Papyan |
| 2024 | Riemannian Preconditioned LoRA for Fine-Tuning Foundation Models. | Fangzhao Zhang, Mert Pilanci |
| 2024 | In-Context Principle Learning from Mistakes. | Tianjun Zhang, Aman Madaan, Luyu Gao, Steven Zheng, Swaroop Mishra, Yiming Yang, Niket Tandon, Uri Alon |
| 2024 | UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis. | Yunhao Zhang, Minghao Liu, Shengyang Zhou, Junchi Yan |
| 2024 | Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples. | Thomas T. C. K. Zhang, Bruce D. Lee, Ingvar M. Ziemann, George J. Pappas, Nikolai Matni |
| 2024 | BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation. | Li Zhang, Youwei Liang, Ruiyi Zhang, Amirhosein Javadi, Pengtao Xie |
| 2024 | Conditional Language Learning with Context. | Xiao Zhang, Miao Li, Ji Wu |
| 2024 | DPZero: Private Fine-Tuning of Language Models without Backpropagation. | Liang Zhang, Bingcong Li, Kiran Koshy Thekumparampil, Sewoong Oh, Niao He |
| 2024 | Understanding Unimodal Bias in Multimodal Deep Linear Networks. | Yedi Zhang, Peter E. Latham, Andrew M. Saxe |
| 2024 | S3O: A Dual-Phase Approach for Reconstructing Dynamic Shape and Skeleton of Articulated Objects from Single Monocular Video. | Hao Zhang, Fang Li, Samyak Rawlekar, Narendra Ahuja |