354 citations · 2.1k across the 86 of their papers we have counts for
8 papers · 1 filter
SEGNO: Generalizing Equivariant Graph Neural Networks with Physical Inductive Biases
Yang Liu, Jiashun Cheng, Haihong Zhao +5
Graph Neural Networks (GNNs) with equivariant properties have emerged as powerful tools for modeling complex dynamics of multi-object physical systems. However, their generalizatio…
DFWLayer: Differentiable Frank-Wolfe Optimization Layer
Zixuan Liu, Liu Liu, Xueqian Wang +1
Differentiable optimization has received a significant amount of attention due to its foundational role in the domain of machine learning based on neural networks. This paper propo…
GADBench: Revisiting and Benchmarking Supervised Graph Anomaly Detection
Jianheng Tang, Fengrui Hua, Ziqi Gao +2
With a long history of traditional Graph Anomaly Detection (GAD) algorithms and recently popular Graph Neural Networks (GNNs), it is still not clear (1) how they perform under a st…
Attention Paper: How Generative AI Reshapes Digital Shadow Industry?
Qichao Wang, Huan Ma, Wentao Wei +8
The rapid development of digital economy has led to the emergence of various black and shadow internet industries, which pose potential risks that can be identified and managed thr…
Reweighted Mixup for Subpopulation Shift
Zongbo Han, Zhipeng Liang, Fan Yang +8
Subpopulation shift exists widely in many real-world applications, which refers to the training and test distributions that contain the same subpopulation groups but with different…
Fairness-guided Few-shot Prompting for Large Language Models
Huan Ma, Changqing Zhang, Yatao Bian +7
Large language models have demonstrated surprising ability to perform in-context learning, i.e., these models can be directly applied to solve numerous downstream tasks by conditio…
Deploying Offline Reinforcement Learning with Human Feedback
Ziniu Li, Ke Xu, Liu Liu +3
Reinforcement learning (RL) has shown promise for decision-making tasks in real-world applications. One practical framework involves training parameterized policy models from an of…
Towards Stable Test-Time Adaptation in Dynamic Wild World
Shuaicheng Niu, Jiaxiang Wu, Yifan Zhang +4
Test-time adaptation (TTA) has shown to be effective at tackling distribution shifts between training and testing data by adapting a given model on test samples. However, the onlin…