| 2024 | Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling. | Mingze Wang, Zeping Min, Lei Wu |
| 2024 | MC-GTA: Metric-Constrained Model-Based Clustering using Goodness-of-fit Tests with Autocorrelations. | Zhangyu Wang, Gengchen Mai, Krzysztof Janowicz, Ni Lao |
| 2024 | A Dual-module Framework for Counterfactual Estimation over Time. | Xin Wang, Shengfei Lyu, Lishan Yang, Yibing Zhan, Huanhuan Chen |
| 2024 | EfficientZero V2: Mastering Discrete and Continuous Control with Limited Data. | Shengjie Wang, Shaohuai Liu, Weirui Ye, Jiacheng You, Yang Gao |
| 2024 | An Iterative Min-Min Optimization Method for Sparse Bayesian Learning. | Yasen Wang, Junlin Li, Zuogong Yue, Ye Yuan |
| 2024 | MS3D: A RG Flow-Based Regularization for GAN Training with Limited Data. | Jian Wang, Xin Lan, Yuxin Tian, Jiancheng Lv |
| 2024 | Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning. | Xiyu Wang, Baijiong Lin, Daochang Liu, Ying-Cong Chen, Chang Xu |
| 2024 | Highway Value Iteration Networks. | Yuhui Wang, Weida Li, Francesco Faccio, Qingyuan Wu, Jrgen Schmidhuber |
| 2024 | Bootstrap AutoEncoders With Contrastive Paradigm for Self-supervised Gaze Estimation. | Yaoming Wang, Jin Li, Wenrui Dai, Bowen Shi, Xiaopeng Zhang, Chenglin Li, Hongkai Xiong |
| 2024 | StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization. | Shida Wang, Qianxiao Li |
| 2024 | Improving Generalization in Offline Reinforcement Learning via Adversarial Data Splitting. | Da Wang, Lin Li, Wei Wei, Qixian Yu, Jianye Hao, Jiye Liang |
| 2024 | Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models. | Zhengbo Wang, Jian Liang, Ran He, Zilei Wang, Tieniu Tan |
| 2024 | Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions. | Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Chuan-Sheng Foo, Bryan Kian Hsiang Low |
| 2024 | Total Variation Floodgate for Variable Importance Inference in Classification. | Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas |
| 2024 | In-context Learning on Function Classes Unveiled for Transformers. | Zhijie Wang, Bo Jiang, Shuai Li |
| 2024 | EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting. | Jiaxu Wang, Junhao He, Ziyi Zhang, Mingyuan Sun, Jingkai Sun, Renjing Xu |
| 2024 | SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models. | Xiaoxuan Wang, Ziniu Hu, Pan Lu, Yanqiao Zhu, Jieyu Zhang, Satyen Subramaniam, Arjun R. Loomba, Shichang Zhang, Yizhou Sun, Wei Wang |
| 2024 | Mollification Effects of Policy Gradient Methods. | Tao Wang, Sylvia L. Herbert, Sicun Gao |
| 2024 | Rapid Learning without Catastrophic Forgetting in the Morris Water Maze. | Raymond Wang, Jaedong Hwang, Akhilan Boopathy, Ila R. Fiete |
| 2024 | Optimal Kernel Choice for Score Function-based Causal Discovery. | Wenjie Wang, Biwei Huang, Feng Liu, Xinge You, Tongliang Liu, Kun Zhang, Mingming Gong |
| 2024 | Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach. | Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser |
| 2024 | MEMORYLLM: Towards Self-Updatable Large Language Models. | Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian J. McAuley |
| 2024 | Understanding Heterophily for Graph Neural Networks. | Junfu Wang, Yuanfang Guo, Liang Yang, Yunhong Wang |
| 2024 | Optimal Kernel Quantile Learning with Random Features. | Caixing Wang, Xingdong Feng |
| 2024 | Swallowing the Bitter Pill: Simplified Scalable Conformer Generation. | Yuyang Wang, Ahmed A. A. Elhag, Navdeep Jaitly, Joshua M. Susskind, Miguel ngel Bautista |