This work proposes PURE (Purging Unrelated Representations for Content-Agnostic Forgery Detection), which achieves content-agnostic detection through two complementary components: a Causal Semantic Generative (CSG) mechanism that disentangles semantic representations from forgery-irrelevant nuisance factors, and a Gaus...
Xin-Yu Wu, Dong Li, Minglai Shao et al.· Proceedings of the Thirty-Fi...· 0 citations
A message extrapolation mechanism under soft uncertainty constraints is proposed to obtain the diverse counterfactual message distributions and a novel robust representation learning framework for dynamic graph domain generalization, LEMD is proposed.
Xiao-Ran Wei, Chen Zhao, Minglai Shao et al.· Proceedings of the Thirty-Fi...· 0 citations
Deploying Large Language Models (LLMs) over the edge-cloud continuum faces severe stability challenges due to the conflict between stochastic network topology and complex workflow dependencies. Existing schedulers, relying either on computationally prohibitive Graph Neural Networks (GNNs) or topology-agnostic heuristic...
Yan Gao, Shaoyuan Huang, Yonghui Ye et al.· IEEE Transactions on Cogniti...· 0 citations
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