6 papers
Behavioral Skill Reconstruction: Reconstructing Hidden Functionality from LLM Agent Skills
Peichun Hua, Haoxuan Xu, Mengyuan Li
Closed source agent skills may encode proprietary instructions, scripts, constants, and data. Providers may offer their capabilities as services while keeping the underlying packag…
Infrastructure for Valuable, Tradable, and Verifiable Agent Memory
Mengyuan Li, Lei Gao, Haoxuan Xu +5
Every API token you spend is your accumulated wealth; once you can prove its value and the effort behind it, you can resell it. As autonomous agents repeatedly call models and tool…
A Systematic Study of Model Extraction Attacks on Graph Foundation Models
Haoyan Xu, Ruizhi Qian, Jiate Li +9
Graph machine learning has advanced rapidly in tasks such as link prediction, anomaly detection, and node classification. As models scale up, pretrained graph models have become va…
Graph Synthetic Out-of-Distribution Exposure with Large Language Models
Haoyan Xu, Zhengtao Yao, Ziyi Wang +4
Out-of-distribution (OOD) detection in graphs is critical for ensuring model robustness in open-world and safety-sensitive applications. Existing graph OOD detection approaches typ…
GLIP-OOD: Zero-Shot Graph OOD Detection with Graph Foundation Model
Haoyan Xu, Zhengtao Yao, Xuzhi Zhang +6
Out-of-distribution (OOD) detection is critical for ensuring the safety and reliability of machine learning systems, particularly in dynamic and open-world environments. In the vis…
Few-Shot Graph Out-of-Distribution Detection with LLMs
Haoyan Xu, Zhengtao Yao, Yushun Dong +4
Existing methods for graph out-of-distribution (OOD) detection typically depend on training graph neural network (GNN) classifiers using a substantial amount of labeled in-distribu…