5 papers
PhyCheck: Fine-Grained Evidence-Grounded Dataset for Physical Law Understanding in Video-LLMs
Zhongjie Ba, Shengwang Xu, Peng Cheng +4
Embodied intelligence and world models require video understanding systems to go beyond recognizing objects and actions and develop an understanding of physical regularities. Howev…
Channel-Level Semantic Perturbations: Unlearnable Examples for Diverse Training Paradigms
Bo Wang, Jia Ni, Mengnan Zhao +2
The unauthorized use of personal data in model training has emerged as a growing privacy threat. Unlearnable examples (UEs) address this issue by embedding imperceptible perturbati…
Eguard: Defending LLM Embeddings Against Inversion Attacks via Text Mutual Information Optimization
Tiantian Liu, Hongwei Yao, Feng Lin +3
Embeddings have become a cornerstone in the functionality of large language models (LLMs) due to their ability to transform text data into rich, dense numerical representations tha…
WMCopier: Forging Invisible Image Watermarks on Arbitrary Images
Ziping Dong, Chao Shuai, Zhongjie Ba +4
Invisible Image Watermarking is crucial for ensuring content provenance and accountability in generative AI. While Gen-AI providers are increasingly integrating invisible watermark…
Membership Inference Attacks Against Vision-Language Models
Yuke Hu, Zheng Li, Zhihao Liu +4
Vision-Language Models (VLMs), built on pre-trained vision encoders and large language models (LLMs), have shown exceptional multi-modal understanding and dialog capabilities, posi…