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Yujin Huang

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#machine learning Preprint Oct 2026

Dynamic Graph World Modelling: Learning Future Dynamics from Temporal Context

Dynamic graph learning models how entities and their relations evolve from historical observations to predict future graph states. Existing methods do not fully address dynamic graph world modelling, which requires learning transitions from temporal context to future latent graph states. This is difficult for three rea...

Bo Li, Yue Yang, Yu-Jin Huang et al. · 0 citations
Conference Open access Sep 2026

GRASP: Hard-Label Black-Box Malware Evasion with Higher Success, Fewer Queries, and Smaller Perturbations

Gradient-seeded Reinforcement Learning And Stealthy Pruning (GRASP), a three-stage framework that tackles challenges of adversarial attacks on machine learning-based malware detectors, and out-performs baselines, achieving higher attack success with fewer queries and smaller file-size inflation.

Yu-Tong Liu, Jian-Ting Ning, Qi Feng et al. · 1 citation

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