Semantic-level UI Element Injection distracts GUI agents by overlaying safety-aligned UI elements, achieving up to 4.4x higher attack success rates that transfer across models and create persistent attractors.
IEEE Transactions on Big Data (2025)
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
ModuSeg enables training-free weakly supervised semantic segmentation by explicitly separating geometric object discovery from non-parametric semantic feature retrieval using existing mask proposers and foundation model feature banks.
U-CESE integrates three CESE modules into a unified clip-based pipeline with DAKE keyframe extraction and ReCap captioning to support consistent multimodal event retrieval across video sources.
citing papers explorer
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Are GUI Agents Focused Enough? Automated Distraction via Semantic-level UI Element Injection
Semantic-level UI Element Injection distracts GUI agents by overlaying safety-aligned UI elements, achieving up to 4.4x higher attack success rates that transfer across models and create persistent attractors.
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ModuSeg: Decoupling Object Discovery and Semantic Retrieval for Training-Free Weakly Supervised Segmentation
ModuSeg enables training-free weakly supervised semantic segmentation by explicitly separating geometric object discovery from non-parametric semantic feature retrieval using existing mask proposers and foundation model feature banks.
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U-CESE: Unified Clip-based Event Search Engine for AI Challenge HCMC 2025
U-CESE integrates three CESE modules into a unified clip-based pipeline with DAKE keyframe extraction and ReCap captioning to support consistent multimodal event retrieval across video sources.