MLLMs are increasingly deployed in user-facing applications, yet they inherit backdoor risks from the pipelines used to construct them: triggers may reside in images, texts, or both. Existing model-level backdoor removal methods, largely designed for conventional classifiers, show limited effectiveness on MLLMs, while...
Jia-Li Wei, Ming Fan, Ming-Kun Zhang et al.· 0 citations
Test-time scaling improves code generation by spending additional inference budget (e.g., calls or tokens) on direct sampling, feedback-conditioned repair, and reasoning-guided implementation. Search-based methods can allocate this budget adaptively, but two challenges remain. First, tree-structured search treats each...
Xi-Tao Li, Hai-Jun Wang, Ge-Ge Yuan et al.· 0 citations
Standardized token contracts (e.g., ERC-20) form the foundation of digital assets. However, attackers increasingly abuse this standardization to disguise malicious trap tokens. Unlike obvious violations, these contracts employ a strategy of"deceptive adherence": they strictly adhere to standard protocols to evade detec...
Yin Wu, Yi-Xuan Liu, Yi Li et al.· arXiv.org· 1 citation
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