3 papers
cs.CR2026
Data-Chain Backdoor: Do You Trust Diffusion Models as Generative Data Supplier?
Junchi Lu, Xinke Li, Yuheng Liu +1
The increasing use of generative models such as diffusion models for synthetic data augmentation has greatly reduced the cost of data collection and labeling in downstream percepti…
cs.LG2025
Ignoring Directionality Leads to Compromised Graph Neural Network Explanations
Changsheng Sun, Xinke Li, Jin Song Dong
Graph Neural Networks (GNNs) are increasingly used in critical domains, where reliable explanations are vital for supporting human decision-making. However, the common practice of…
cs.LG2025
Learning Against Distributional Uncertainty: On the Trade-off Between Robustness and Specificity
Shixiong Wang, Haowei Wang, Xinke Li +1
Trustworthy machine learning aims at combating distributional uncertainties in training data distributions compared to population distributions. Typical treatment frameworks includ…