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cs.LG2026
Out-of-Distribution Graph Models Merging
Yidi Wang, Ziyue Qiao, Jiawei Gu +4
This paper studies a novel problem of out-of-distribution graph models merging, which aims to construct a generalized model from multiple graph models pre-trained on different doma…
cs.LG2025
AHSG: Adversarial Attack on High-level Semantics in Graph Neural Networks
Kai Yuan, Jiahao Zhang, Yidi Wang +1
Adversarial attacks on Graph Neural Networks aim to perturb the performance of the learner by carefully modifying the graph topology and node attributes. Existing methods achieve a…