5 papers
Universal Adversarial Attacks against Closed-Source MLLMs via Target-View Routed Meta Optimization
Hui Lu, Yi Yu, Yiming Yang +6
Targeted adversarial attacks on closed-source multimodal large language models (MLLMs) have been increasingly explored under black-box transfer, yet prior methods are predominantly…
From Pretrain to Pain: Adversarial Vulnerability of Video Foundation Models Without Task Knowledge
Hui Lu, Yi Yu, Song Xia +5
Large-scale Video Foundation Models (VFMs) has significantly advanced various video-related tasks, either through task-specific models or Multi-modal Large Language Models (MLLMs).…
When Robots Obey the Patch: Universal Transferable Patch Attacks on Vision-Language-Action Models
Hui Lu, Yi Yu, Yiming Yang +5
Vision-Language-Action (VLA) models are vulnerable to adversarial attacks, yet universal and transferable attacks remain underexplored, as most existing patches overfit to a single…
VidLBEval: Benchmarking and Mitigating Language Bias in Video-Involved LVLMs
Yiming Yang, Yangyang Guo, Hui Lu +1
Recently, Large Vision-Language Models (LVLMs) have made significant strides across diverse multimodal tasks and benchmarks. This paper reveals a largely under-explored problem fro…
Efficient Temporal Sentence Grounding in Videos with Multi-Teacher Knowledge Distillation
Renjie Liang, Yiming Yang, Hui Lu +1
Temporal Sentence Grounding in Videos (TSGV) aims to detect the event timestamps described by the natural language query from untrimmed videos. This paper discusses the challenge o…