Author

Chenghua Guo

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#machine learning May 2026

WMAttack: Automated Attack Search for Adversarial Evaluation of World-Model Agents

WMAttack, an automated attack-search framework for adversarial evaluation of world-model agents, is introduced and a theoretical explanation showing that proposal refinement improves finite-budget search when it shifts probability mass toward high-utility attacks is provided.

Zhixiang Guo, Si-Yuan Liang, Shi Fu et al. · arXiv.org · 6 citations