Cover Image

Adversarial Robustness for Visual Grounding of Multimodal Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Gao, Kuofeng, Bai, Yang, Bai, Jiawang, Yang, Yong, Xia, Shu-Tao
Format:	Preprint
Published:	2024
Subjects:	Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIP
by: Bai, Jiawang, et al.
Published: (2023)

Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers
by: Yang, Sheng, et al.
Published: (2024)

Towards Dataset Copyright Evasion Attack against Personalized Text-to-Image Diffusion Models
by: Gao, Kuofeng, et al.
Published: (2025)

Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images
by: Gao, Kuofeng, et al.
Published: (2024)

FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs
by: Li, Jinmin, et al.
Published: (2024)

Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples
by: Gao, Kuofeng, et al.
Published: (2024)

Video Watermarking: Safeguarding Your Video from (Unauthorized) Annotations by Video-based LLMs
by: Li, Jinmin, et al.
Published: (2024)

Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs
by: Fang, Hao, et al.
Published: (2025)

Protecting Your Video Content: Disrupting Automated Video-based LLM Annotations
by: Liu, Haitong, et al.
Published: (2025)

Revisiting the Adversarial Robustness of Vision Language Models: a Multimodal Perspective
by: Zhou, Wanqi, et al.
Published: (2024)

Seeing Through the Chain: Mitigate Hallucination in Multimodal Reasoning Models via CoT Compression and Contrastive Preference Optimization
by: Fang, Hao, et al.
Published: (2026)

GroundVTS: Visual Token Sampling in Multimodal Large Language Models for Video Temporal Grounding
by: Fan, Rong, et al.
Published: (2026)

Survey of Adversarial Robustness in Multimodal Large Language Models
by: Jiang, Chengze, et al.
Published: (2025)

Pre-training CLIP against Data Poisoning with Optimal Transport-based Matching and Alignment
by: Zhang, Tong, et al.
Published: (2025)

On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression
by: Zhang, Xinwei, et al.
Published: (2026)

From Generalist to Specialist: Adapting Vision Language Models via Task-Specific Visual Instruction Tuning
by: Bai, Yang, et al.
Published: (2024)

DocThinker: Explainable Multimodal Large Language Models with Rule-based Reinforcement Learning for Document Understanding
by: Yu, Wenwen, et al.
Published: (2025)

VLMInferSlow: Evaluating the Efficiency Robustness of Large Vision-Language Models as a Service
by: Wang, Xiasi, et al.
Published: (2025)

Parameter-Efficient and Memory-Efficient Tuning for Vision Transformer: A Disentangled Approach
by: Zhang, Taolin, et al.
Published: (2024)

EndoChat: Grounded Multimodal Large Language Model for Endoscopic Surgery
by: Wang, Guankun, et al.
Published: (2025)

Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
by: Lu, Zhihe, et al.
Published: (2023)

A Refer-and-Ground Multimodal Large Language Model for Biomedicine
by: Huang, Xiaoshuang, et al.
Published: (2024)

Grounded Chain-of-Thought for Multimodal Large Language Models
by: Wu, Qiong, et al.
Published: (2025)

Retrievals Can Be Detrimental: Unveiling the Backdoor Vulnerability of Retrieval-Augmented Diffusion Models
by: Fang, Hao, et al.
Published: (2025)

Adversarial Prompt Injection Attack on Multimodal Large Language Models
by: Ding, Meiwen, et al.
Published: (2026)

TokenCarve: Information-Preserving Visual Token Compression in Multimodal Large Language Models
by: Tan, Xudong, et al.
Published: (2025)

GeoGround: A Unified Large Vision-Language Model for Remote Sensing Visual Grounding
by: Zhou, Yue, et al.
Published: (2024)

MMT-ARD: Multimodal Multi-Teacher Adversarial Distillation for Robust Vision-Language Models
by: Li, Yuqi, et al.
Published: (2025)

EgoActor: Grounding Task Planning into Spatial-aware Egocentric Actions for Humanoid Robots via Visual-Language Models
by: Bai, Yu, et al.
Published: (2026)

Benchmarking and Improving Large Vision-Language Models for Fundamental Visual Graph Understanding and Reasoning
by: Zhu, Yingjie, et al.
Published: (2024)

DUALVISION: RGB-Infrared Multimodal Large Language Models for Robust Visual Reasoning
by: Majeedi, Abrar, et al.
Published: (2026)

Multimodal Large Language Model-Enabled Video Translation: A Role-Oriented Survey
by: Qu, Bingzheng, et al.
Published: (2026)

OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models
by: Yu, Wenwen, et al.
Published: (2025)

Improving Adversarial Robustness via Decoupled Visual Representation Masking
by: Liu, Decheng, et al.
Published: (2024)

Grounding Everything in Tokens for Multimodal Large Language Models
by: Ren, Xiangxuan, et al.
Published: (2025)

ViGoR: Improving Visual Grounding of Large Vision Language Models with Fine-Grained Reward Modeling
by: Yan, Siming, et al.
Published: (2024)

Hallucination of Multimodal Large Language Models: A Survey
by: Bai, Zechen, et al.
Published: (2024)

GeM-VG: Towards Generalized Multi-image Visual Grounding with Multimodal Large Language Models
by: Zheng, Shurong, et al.
Published: (2026)

ReFIR: Grounding Large Restoration Models with Retrieval Augmentation
by: Guo, Hang, et al.
Published: (2024)

LLMGA: Multimodal Large Language Model based Generation Assistant
by: Xia, Bin, et al.
Published: (2023)