3 papers
cs.LG2026
WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents
Zhixiang Guo, Siyuan Liang, Shi Fu +4
Despite the growing use of world models as decision-making agents, their adversarial robustness remains underexplored due to the lack of dedicated automated evaluation methods. A k…
cs.LG2026
Uncertainty Quantification on Graph Learning: A Survey
Chao Chen, Chenghua Guo, Rui Xu +6
Graphical models have demonstrated their exceptional capabilities across numerous applications. However, their performance, confidence, and trustworthiness are often limited by the…
cs.LG2024
Provable Robust Saliency-based Explanations
Chao Chen, Chenghua Guo, Rufeng Chen +5
To foster trust in machine learning models, explanations must be faithful and stable for consistent insights. Existing relevant works rely on the distance for stability as…