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cs.LG2026
WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents
Zhixiang Guo, Siyuan Liang, Shi Fu +4
Despite the growing use of world models as decision-making agents, their adversarial robustness remains underexplored due to the lack of dedicated automated evaluation methods. A k…
cs.LG2026
When World Models Dream Wrong: Physical-Conditioned Adversarial Attacks against World Models
Zhixiang Guo, Siyuan Liang, Andras Balogh +4
Generative world models (WMs) are increasingly used to synthesize controllable, sensor-conditioned driving videos, yet their reliance on physical priors exposes novel attack surfac…
cs.LG2026
Verification of the Implicit World Model in a Generative Model via Adversarial Sequences
András Balogh, Márk Jelasity
Generative sequence models are typically trained on sample sequences from natural or formal languages. It is a crucial question whether -- or to what extent -- sample-based trainin…