collaborators

7 papers

cs.CR2026

SkillSentry: Adaptive Honey Worlds for Dynamic Safety Testing of Agent Skills

Nizhang Li, Zonghao Ying, Xiangfan Wu +7

External skills extend the capabilities of large language model agents, but also introduce an execution-time attack surface: a skill that appears benign under inspection may reveal…

cs.MA2026

SafeFlow: Semantic Information-Flow Control for Blocking Malicious Propagation in Multi-Agent Systems

Haowen Dai, Zonghao Ying, Wenfeng Li +10

Multi-agent systems improve capability through task decomposition and role specialization, but these same mechanisms introduce an important safety blind spot: a harmful objective c…

cs.CL2026

Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion

Jiawei Sheng, Taoyu Su, Xixun Lin +2

Multi-domain knowledge graph completion (MKGC) aims to improve missing triple prediction in a target KG by transferring knowledge from other support KGs. Existing methods typically…

cs.LG2026

Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation

Shuai Zhang, Yancheng Chen, Chuan Zhou +5

Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including social networks, medical diagnosis,…

cs.LG2026

Message Tuning Outshines Graph Prompt Tuning: A Prismatic Space Perspective

Yancheng Chen, Dun Ma, Shuai Zhang +6

Graph Foundation Models (GFMs), built upon the Pre-training and Adaptation paradigm, have emerged as a research hotspot in graph learning. For GNN-based GFMs, graph prompt tuning h…

cs.LG2026

AbstainGNN: Teaching Graph Neural Networks to Abstain for Graph Classification

Xixun Lin, Zhiheng Zhou, Zhengyin Zhang +9

Graph classification is a core task in graph data mining with widespread real-world applications. Recent advances in graph neural networks (GNNs) have led to substantial performanc…