Papers
Beyond Monotonicity: Revisiting Factorization Principles in Multi-Agent Q-Learning
Tianmeng Hu, Yongzheng Cui, Rui Tang et al.
Prototype-Based Semantic Consistency Alignment for Domain Adaptive Retrieval
Tianle Hu, Weijun Lv, Na Han et al.
FedLAGC: Towards High Performance System-Heterogeneous Federated Learning via Layer-Adaptive Submodel Extraction and Gradient Correction
Qing Hu, Tianchi Liao, Shuyi Wu et al.
FedTopo: Topology-Informed Representation Alignment in Federated Learning Under Non-I.I.D. Conditions
Ke Hu, Liyao Xiang, Peng Tang et al.
Look Closer! An Adversarial Parametric Editing Framework for Hallucination Mitigation in VLMs
Jiayu Hu, Beibei Li, Jiangwei Xia et al.
Hyper-Opinion Vagueness Quantification for Robust Multimodal Learning
Disen Hu, Xun Jiang, Xiaofeng Cao et al.
Invariant Conditional Molecular Generation Under Distribution Shift
Chunyu Hu, Tianyin Liao, Yicheng Sui et al.
Venom: Liquid Diffusion-Guided Gradient Inversion for Breaking Differential Privacy in Federated Learning
Bin Hu, Jingling Yuan, Jiawei Jiang et al.
Denoising Mixup for Regression
Zhengzhang Hou, Zhanshan Li, Yanbo Liu et al.
Graph Out-of-Distribution Detection via Test-Time Calibration with Dual Dynamic Dictionaries
Yue Hou, Ruomei Liu, Yingke Su et al.
A Theoretical Analysis of Detecting Large Model-Generated Time Series
Junji Hou, Junzhou Zhao, Shuo Zhang et al.
Gradient-Protected Value Decomposition for Cooperative Multi-Agent Reinforcement Learning
Jie Hou, Haowen Dou, Lujuan Dang et al.
Harmonic Dataset Distillation for Time Series Forecasting
Seungha Hong, Sanghwan Jang, Wonbin Kweon et al.
Lost in Time? A Meta-Learning Framework for Time-Shift-Tolerant Physiological Signal Transformation
Qian Hong, Cheng Bian, Xiao Zhou et al.
HINPool: A Unified Heterogeneous Graph Pooling Framework for Accurate Molecular and Protein Property Prediction
Ming-Yi Hong, You-Chen Teng, Shao-En Lin et al.
Distributional Priors Guided Diffusion for Generating 3D Molecules in Low Data Regimes
Haokai Hong, Wanyu Lin, Ming Yang et al.
From Attribution to Action: Jointly ALIGNing Predictions and Explanations
Dongsheng Hong, Chao Chen, Yanhui Chen et al.
Uncertainty Quantification for Machine Learning: One Size Does Not Fit All
Paul Hofman, Yusuf Sale, Eyke Hüllermeier
Beyond Fixed Depth: Adaptive Graph Neural Networks for Node Classification Under Varying Homophily
Asela Hevapathige, Asiri Wijesinghe, Ahad N. Zehmakan
Posterior Label Smoothing for Node Classification
Jaeseung Heo, MoonJeong Park, Dongwoo Kim
Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models
Zhixia He, Chen Zhao, Minglai Shao et al.
Harnessing Vision-Language Models for Time Series Anomaly Detection
Zelin He, Sarah Alnegheimish, Matthew Reimherr
Deferred Poisoning: Making the Model More Vulnerable via Hessian Singularization
Yuhao He, Jinyu Tian, Xianwei Zheng et al.
Dual Mamba for Node-Specific Representation Learning: Tackling Over-Smoothing with Selective State Space Modeling
Xin He, Yili Wang, Yiwei Dai et al.
A Stage-Aware Mixture of Experts Framework for Neurodegenerative Disease Progression Modelling
Tiantian He, Keyue Jiang, An Zhao et al.