OS-SPEAR is a new evaluation toolkit that tests 22 OS agents and identifies trade-offs between efficiency and safety or robustness.
arXiv preprint arXiv:2508.09456 (2025) 21
4 Pith papers cite this work. Polarity classification is still indexing.
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ProjLens shows that backdoor parameters in MLLMs are encoded in low-rank subspaces of the projector and that embeddings shift toward the target direction with magnitude linear in input norm, activating only on poisoned samples.
Phantasia is a new backdoor attack on VLMs that dynamically aligns malicious outputs with input context to achieve higher stealth and state-of-the-art success rates compared to static-pattern attacks.
Constraining visual token budget per observation during VLM training forces genuine active perception and delivers 5% average relative improvement without auxiliary losses or architecture changes.
citing papers explorer
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OS-SPEAR: A Toolkit for the Safety, Performance,Efficiency, and Robustness Analysis of OS Agents
OS-SPEAR is a new evaluation toolkit that tests 22 OS agents and identifies trade-offs between efficiency and safety or robustness.
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ProjLens: Unveiling the Role of Projectors in Multimodal Model Safety
ProjLens shows that backdoor parameters in MLLMs are encoded in low-rank subspaces of the projector and that embeddings shift toward the target direction with magnitude linear in input norm, activating only on poisoned samples.
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Phantasia: Context-Adaptive Backdoors in Vision Language Models
Phantasia is a new backdoor attack on VLMs that dynamically aligns malicious outputs with input context to achieve higher stealth and state-of-the-art success rates compared to static-pattern attacks.
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Starve to Perceive: Taming Lazy Perception in VLMs with Constrained Visual Bandwidth
Constraining visual token budget per observation during VLM training forces genuine active perception and delivers 5% average relative improvement without auxiliary losses or architecture changes.