GNN prompting aims to adapt models across tasks and graphs without requiring extensive retraining. However, most existing graph prompt methods still require task-specific parameter updates and face the issue of generalizing across graphs, limiting their performance and undermining the core promise of prompting. In this...
Yaqi Chen, Shi-Xun Huang, Lei Wang et al.· Neural Networks· 0 citations
GatorTrio is proposed, a topology-refined tri-view graph learning framework that adaptively fuses views per unit via an interaction-aware sparse Mixture-of-Experts (MoE) router and refine topology through self-training by pruning pseudo-label–inconsistent inter-cluster edges and re-encoding on the refined graphs.
Zhenhao Zhang, Jun Shen, Jiang Bian et al.· Proceedings of the 32nd ACM...· 0 citations
Edge devices handle sensitive user data, raising significant security and privacy concerns when shared with data collectors for downstream learning tasks. One potential solution leverages differentially private generative models, keeping original data on user devices and creating obfuscated variants for transmission. H...
Adil Sarwar, Yanlong Zhai, Jun Shen et al.· IEEE Transactions on Mobile...· 0 citations
The proposed SiPo (Silencing the Poison), a novel framework that shifts the paradigm from node removal to gradient silencing, leverages unsupervised granular ball computing to adaptively capture adversarial topological micro-clusters within the feature space.
Yunmeng Zhao, Jun Shen, Shen-Bao Yu et al.· Proceedings of the 32nd ACM...· 0 citations
Mobile edge computing (MEC) accelerates Internet of Things (IoT) applications by caching content near end users. However, cached data remains vulnerable to corruption, misleading applications, and eroding user trust. Traditional centralized edge data integrity verification (EDIV) methods adopt challenge-response protoc...
Adil Sarwar, Yanlong Zhai, Jun Shen et al.· IEEE Internet of Things Jour...· 0 citations
In many advanced recommender systems (e.g., GNN-based), local smoothing mechanisms would distill collaborative signals but could inadvertently amplify targeted data poisoning threats. Existing defenses predominantly relied on rigid binary filtration strategies. However, such structural deletion of suspicious nodes ofte...
Yunmeng Zhao, Jun Shen, Shenbao Yu et al.· Proceedings of the 32nd ACM...· 0 citations
Spatial domain identification in spatial transcriptomics (ST) partitions a tissue section into spatially coherent regions with distinct transcriptional programs. Recent graph-based approaches construct a spatial neighborhood graph and/or an expression-similarity graph and perform unsupervised domain identification with...
Zhenhao Zhang, Jun Shen, Jiang Bian et al.· Proceedings of the 32nd ACM...· 0 citations
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