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.
Proceedings of the IEEE conference on computer vision and pattern recognition , pages=
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Dual-Anchoring Framework mitigates progress drift via structured instruction tokens and memory drift via landmark-centric retrospective prediction, yielding 15.2% success rate gain and 24.7% on long trajectories.
HRNav decomposes image-goal navigation into VLM-based short-horizon planning and RL-based execution with a wandering suppression penalty to improve performance in complex unseen settings.
citing papers explorer
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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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Dual-Anchoring: Addressing State Drift in Vision-Language Navigation
Dual-Anchoring Framework mitigates progress drift via structured instruction tokens and memory drift via landmark-centric retrospective prediction, yielding 15.2% success rate gain and 24.7% on long trajectories.
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Think before Go: Hierarchical Reasoning for Image-goal Navigation
HRNav decomposes image-goal navigation into VLM-based short-horizon planning and RL-based execution with a wandering suppression penalty to improve performance in complex unseen settings.