| 2024 | Low-Cost High-Power Membership Inference Attacks. | Sajjad Zarifzadeh, Philippe Liu, Reza Shokri |
| 2024 | Robustly Learning Single-Index Models via Alignment Sharpness. | Nikos Zarifis, Puqian Wang, Ilias Diakonikolas, Jelena Diakonikolas |
| 2024 | Robust Yet Efficient Conformal Prediction Sets. | Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski |
| 2024 | DiffAug: Enhance Unsupervised Contrastive Learning with Domain-Knowledge-Free Diffusion-based Data Augmentation. | Zelin Zang, Hao Luo, Kai Wang, Panpan Zhang, Fan Wang, Stan Z. Li, Yang You |
| 2024 | See More Details: Efficient Image Super-Resolution by Experts Mining. | Eduard Zamfir, Zongwei Wu, Nancy Mehta, Yulun Zhang, Radu Timofte |
| 2024 | How to Explore with Belief: State Entropy Maximization in POMDPs. | Riccardo Zamboni, Duilio Cirino, Marcello Restelli, Mirco Mutti |
| 2024 | More Flexible PAC-Bayesian Meta-Learning by Learning Learning Algorithms. | Hossein Zakerinia, Amin Behjati, Christoph H. Lampert |
| 2024 | Sample as you Infer: Predictive Coding with Langevin Dynamics. | Umais Zahid, Qinghai Guo, Zafeirios Fountas |
| 2024 | Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution. | Eslam Zaher, Maciej Trzaskowski, Quan Nguyen, Fred Roosta |
| 2024 | A Unified Adaptive Testing System Enabled by Hierarchical Structure Search. | Junhao Yu, Yan Zhuang, Zhenya Huang, Qi Liu, Xin Li, Rui Li, Enhong Chen |
| 2024 | Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling. | Guoqi Yu, Jing Zou, Xiaowei Hu, Angelica I. Avils-Rivero, Jing Qin, Shujun Wang |
| 2024 | MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities. | Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, Lijuan Wang |
| 2024 | Few-Shot Character Understanding in Movies as an Assessment to Meta-Learning of Theory-of-Mind. | Mo Yu, Qiujing Wang, Shunchi Zhang, Yisi Sang, Kangsheng Pu, Zekai Wei, Han Wang, Liyan Xu, Jing Li, Yue Yu, Jie Zhou |
| 2024 | Purify Unlearnable Examples via Rate-Constrained Variational Autoencoders. | Yi Yu, Yufei Wang, Song Xia, Wenhan Yang, Shijian Lu, Yap-Peng Tan, Alex C. Kot |
| 2024 | Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration. | Zhongzhi Yu, Zheng Wang, Yonggan Fu, Huihong Shi, Khalid Shaikh, Yingyan Celine Lin |
| 2024 | ViP: A Differentially Private Foundation Model for Computer Vision. | Yaodong Yu, Maziar Sanjabi, Yi Ma, Kamalika Chaudhuri, Chuan Guo |
| 2024 | Learning Causal Dynamics Models in Object-Oriented Environments. | Zhongwei Yu, Jingqing Ruan, Dengpeng Xing |
| 2024 | Enabling Few-Shot Learning with PID Control: A Layer Adaptive Optimizer. | Le Yu, Xinde Li, Pengfei Zhang, Zhentong Zhang, Fir Dunkin |
| 2024 | Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring. | Wei Yu, Jianing Li, Shengping Zhang, Xiangyang Ji |
| 2024 | Generalization Bound and New Algorithm for Clean-Label Backdoor Attack. | Lijia Yu, Shuang Liu, Yibo Miao, Xiao-Shan Gao, Lijun Zhang |
| 2024 | Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders. | Xue Yu, Muchen Li, Yan Leng, Renjie Liao |
| 2024 | Privacy-Preserving Instructions for Aligning Large Language Models. | Da Yu, Peter Kairouz, Sewoong Oh, Zheng Xu |
| 2024 | Collage: Light-Weight Low-Precision Strategy for LLM Training. | Tao Yu, Gaurav Gupta, Karthick Gopalswamy, Amith R. Mamidala, Hao Zhou, Jeffrey Huynh, Youngsuk Park, Ron Diamant, Anoop Deoras, Luke Huan |
| 2024 | Activation-Descent Regularization for Input Optimization of ReLU Networks. | Hongzhan Yu, Sicun Gao |
| 2024 | Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge. | Conghan Yue, Zhengwei Peng, Junlong Ma, Shiyan Du, Pengxu Wei, Dongyu Zhang |