| 2024 | Protein Conformation Generation via Force-Guided SE(3) Diffusion Models. | Yan Wang, Lihao Wang, Yuning Shen, Yiqun Wang, Huizhuo Yuan, Yue Wu, Quanquan Gu |
| 2024 | FADAS: Towards Federated Adaptive Asynchronous Optimization. | Yujia Wang, Shiqiang Wang, Songtao Lu, Jinghui Chen |
| 2024 | Defense against Model Extraction Attack by Bayesian Active Watermarking. | Zhenyi Wang, Yihan Wu, Heng Huang |
| 2024 | AD3: Implicit Action is the Key for World Models to Distinguish the Diverse Visual Distractors. | Yucen Wang, Shenghua Wan, Le Gan, Shuai Feng, De-Chuan Zhan |
| 2024 | Benchmarking Deletion Metrics with the Principled Explanations. | Yipei Wang, Xiaoqian Wang |
| 2024 | Optimal Exact Recovery in Semi-Supervised Learning: A Study of Spectral Methods and Graph Convolutional Networks. | Haixiao Wang, Zhichao Wang |
| 2024 | CW Complex Hypothesis for Image Data. | Yi Wang, Zhiren Wang |
| 2024 | Transformers Provably Learn Sparse Token Selection While Fully-Connected Nets Cannot. | Zixuan Wang, Stanley Wei, Daniel Hsu, Jason D. Lee |
| 2024 | Probabilistic Conceptual Explainers: Trustworthy Conceptual Explanations for Vision Foundation Models. | Hengyi Wang, Shiwei Tan, Hao Wang |
| 2024 | Integrated Hardware Architecture and Device Placement Search. | Irene Wang, Jakub Tarnawski, Amar Phanishayee, Divya Mahajan |
| 2024 | RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback. | Yufei Wang, Zhanyi Sun, Jesse Zhang, Zhou Xian, Erdem Biyik, David Held, Zackory Erickson |
| 2024 | The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline. | Haonan Wang, Qianli Shen, Yao Tong, Yang Zhang, Kenji Kawaguchi |
| 2024 | Distributed High-Dimensional Quantile Regression: Estimation Efficiency and Support Recovery. | Caixing Wang, Ziliang Shen |
| 2024 | How to Trace Latent Generative Model Generated Images without Artificial Watermark? | Zhenting Wang, Vikash Sehwag, Chen Chen, Lingjuan Lyu, Dimitris N. Metaxas, Shiqing Ma |
| 2024 | A Fine-grained Analysis of Fitted Q-evaluation: Beyond Parametric Models. | Jiayi Wang, Zhengling Qi, Raymond K. W. Wong |
| 2024 | Proteus: Exploring Protein Structure Generation for Enhanced Designability and Efficiency. | Chentong Wang, Yannan Qu, Zhangzhi Peng, Yukai Wang, Hongli Zhu, Dachuan Chen, Longxing Cao |
| 2024 | Efficient Online Set-valued Classification with Bandit Feedback. | Zhou Wang, Xingye Qiao |
| 2024 | Probabilistic Constrained Reinforcement Learning with Formal Interpretability. | Yanran Wang, Qiuchen Qian, David Boyle |
| 2024 | InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining. | Boxin Wang, Wei Ping, Lawrence McAfee, Peng Xu, Bo Li, Mohammad Shoeybi, Bryan Catanzaro |
| 2024 | Sample Average Approximation for Conditional Stochastic Optimization with Dependent Data. | Yafei Wang, Bo Pan, Mei Li, Jianya Lu, Lingchen Kong, Bei Jiang, Linglong Kong |
| 2024 | Pi-DUAL: Using privileged information to distinguish clean from noisy labels. | Ke Wang, Guillermo Ortiz-Jimnez, Rodolphe Jenatton, Mark Collier, Efi Kokiopoulou, Pascal Frossard |
| 2024 | More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning. | Kaiwen Wang, Owen Oertell, Alekh Agarwal, Nathan Kallus, Wen Sun |
| 2024 | TroVE: Inducing Verifiable and Efficient Toolboxes for Solving Programmatic Tasks. | Zhiruo Wang, Graham Neubig, Daniel Fried |
| 2024 | Transforming and Combining Rewards for Aligning Large Language Models. | Zihao Wang, Chirag Nagpal, Jonathan Berant, Jacob Eisenstein, Alexander Nicholas D'Amour, Sanmi Koyejo, Victor Veitch |
| 2024 | EvoluNet: Advancing Dynamic Non-IID Transfer Learning on Graphs. | Haohui Wang, Yuzhen Mao, Yujun Yan, Yaoqing Yang, Jianhui Sun, Kevin Choi, Balaji Veeramani, Alison Hu, Edward Bowen, Tyler Cody, Dawei Zhou |