8 papers
Toward Polymorphic Backdoor against Semantic Communication via Intensity-Based Poisoning
Xiao Yang, Yuni Lai, Gaolei Li +4
Semantic Communication (SC) backdoor attacks aim to utilize triggers to manipulate the system into producing predetermined outputs via backdoored shared knowledge. Current SC backd…
Stealthy Dual-Trigger Backdoors: Attacking Prompt Tuning in LM-Empowered Graph Foundation Models
Xiaoyu Xue, Yuni Lai, Chenxi Huang +4
The emergence of graph foundation models (GFMs), particularly those incorporating language models (LMs), has revolutionized graph learning and demonstrated remarkable performance o…
Provably Robust Adaptation for Language-Empowered Foundation Models
Yuni Lai, Xiaoyu Xue, Linghui Shen +5
Language-empowered foundation models (LeFMs), such as CLIP and GraphCLIP, have transformed multimodal learning by aligning visual (or graph) features with textual representations,…
Adversarial Robustness of Link Sign Prediction in Signed Graphs
Jialong Zhou, Xing Ai, Yuni Lai +7
Signed graphs serve as fundamental data structures for representing positive and negative relationships in social networks, with signed graph neural networks (SGNNs) emerging as th…
Towards Robust Graph Structural Learning Beyond Homophily via Preserving Neighbor Similarity
Yulin Zhu, Yuni Lai, Xing Ai +7
Despite the tremendous success of graph-based learning systems in handling structural data, it has been widely investigated that they are fragile to adversarial attacks on homophil…
Multi-Grained Temporal-Spatial Graph Learning for Stable Traffic Flow Forecasting
Zhenan Lin, Yuni Lai, Wai Lun Lo +5
Time-evolving traffic flow forecasting are playing a vital role in intelligent transportation systems and smart cities. However, the dynamic traffic flow forecasting is a highly no…