Cover Image

MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Pi, Renjie, Han, Tianyang, Zhang, Jianshu, Xie, Yueqi, Pan, Rui, Lian, Qing, Dong, Hanze, Zhang, Jipeng, Zhang, Tong
Format:	Preprint
Published:	2024
Subjects:	Cryptography and Security Computation and Language Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GradSafe: Detecting Jailbreak Prompts for LLMs via Safety-Critical Gradient Analysis
by: Xie, Yueqi, et al.
Published: (2024)

DualTAP: A Dual-Task Adversarial Protector for Mobile MLLM Agents
by: Zhang, Fuyao, et al.
Published: (2025)

Backdoor Cleaning without External Guidance in MLLM Fine-tuning
by: Rong, Xuankun, et al.
Published: (2025)

The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative
by: Tan, Zhen, et al.
Published: (2024)

Root Defence Strategies: Ensuring Safety of LLM at the Decoding Level
by: Zeng, Xinyi, et al.
Published: (2024)

Mind the Third Eye! Benchmarking Privacy Awareness in MLLM-powered Smartphone Agents
by: Lin, Zhixin, et al.
Published: (2025)

Technical Report for ICML 2024 TiFA Workshop MLLM Attack Challenge: Suffix Injection and Projected Gradient Descent Can Easily Fool An MLLM
by: Guo, Yangyang, et al.
Published: (2024)

Medical MLLM is Vulnerable: Cross-Modality Jailbreak and Mismatched Attacks on Medical Multimodal Large Language Models
by: Huang, Xijie, et al.
Published: (2024)

Personalized Visual Instruction Tuning
by: Pi, Renjie, et al.
Published: (2024)

Enhanced MLLM Black-Box Jailbreaking Attacks and Defenses
by: Zhong, Xingwei, et al.
Published: (2025)

Image Textualization: An Automatic Framework for Creating Accurate and Detailed Image Descriptions
by: Pi, Renjie, et al.
Published: (2024)

Safety is Not Only About Refusal: Reasoning-Enhanced Fine-tuning for Interpretable LLM Safety
by: Zhang, Yuyou, et al.
Published: (2025)

PandaGuard: Systematic Evaluation of LLM Safety against Jailbreaking Attacks
by: Shen, Guobin, et al.
Published: (2025)

Event Trojan: Asynchronous Event-based Backdoor Attacks
by: Wang, Ruofei, et al.
Published: (2024)

AEIOU: A Unified Defense Framework against NSFW Prompts in Text-to-Image Models
by: Wang, Yiming, et al.
Published: (2024)

Understanding and Mitigating Over-refusal for Large Language Models via Safety Representation
by: Zhang, Junbo, et al.
Published: (2025)

The Instinctive Bias: Spurious Images lead to Illusion in MLLMs
by: Han, Tianyang, et al.
Published: (2024)

Overlooked Safety Vulnerability in LLMs: Malicious Intelligent Optimization Algorithm Request and its Jailbreak
by: Gu, Haoran, et al.
Published: (2026)

SafeAligner: Safety Alignment against Jailbreak Attacks via Response Disparity Guidance
by: Huang, Caishuang, et al.
Published: (2024)

Benchmarking and Understanding Safety Risks in AI Character Platforms
by: Wei, Yiluo, et al.
Published: (2025)

Trigger Where It Hurts: Unveiling Hidden Backdoors through Sensitivity with Sensitron
by: Zhao, Gejian, et al.
Published: (2025)

One Trigger Token Is Enough: A Defense Strategy for Balancing Safety and Usability in Large Language Models
by: Gu, Haoran, et al.
Published: (2025)

SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From
by: Tong, Yao, et al.
Published: (2025)

Large Language Models are Good Attackers: Efficient and Stealthy Textual Backdoor Attacks
by: Li, Ziqiang, et al.
Published: (2024)

Model-Agnostic Lifelong LLM Safety via Externalized Attack-Defense Co-Evolution
by: Zhang, Xiaozhe, et al.
Published: (2026)

Be Your Own Red Teamer: Safety Alignment via Self-Play and Reflective Experience Replay
by: Wang, Hao, et al.
Published: (2026)

DataShield: Safety-degrading Data Filtering for LLM Benign Instruction Fine-Tuning
by: Zhang, Junbo, et al.
Published: (2026)

Q-MLLM: Vector Quantization for Robust Multimodal Large Language Model Security
by: Zhao, Wei, et al.
Published: (2025)

Evolving Contextual Safety in Multi-Modal Large Language Models via Inference-Time Self-Reflective Memory
by: Zhang, Ce, et al.
Published: (2026)

Cross-Task Defense: Instruction-Tuning LLMs for Content Safety
by: Fu, Yu, et al.
Published: (2024)

Membership Inference Attacks Against In-Context Learning
by: Wen, Rui, et al.
Published: (2024)

Majority Bit-Aware Watermarking For Large Language Models
by: Xu, Jiahao, et al.
Published: (2025)

Contextualized Privacy Defense for LLM Agents
by: Wen, Yule, et al.
Published: (2026)

Challenges in Ensuring AI Safety in DeepSeek-R1 Models: The Shortcomings of Reinforcement Learning Strategies
by: Parmar, Manojkumar, et al.
Published: (2025)

Jailbreak Antidote: Runtime Safety-Utility Balance via Sparse Representation Adjustment in Large Language Models
by: Shen, Guobin, et al.
Published: (2024)

DAVSP: Safety Alignment for Large Vision-Language Models via Deep Aligned Visual Safety Prompt
by: Zhang, Yitong, et al.
Published: (2025)

Analyzing Codes of Conduct for Online Safety in Video Games at Scale
by: Jiang, Jiuming, et al.
Published: (2026)

Omni-Safety under Cross-Modality Conflict: Vulnerabilities, Dynamics Mechanisms and Efficient Alignment
by: Wang, Kun, et al.
Published: (2026)

Automated Progressive Red Teaming
by: Jiang, Bojian, et al.
Published: (2024)

BadLingual: A Novel Lingual-Backdoor Attack against Large Language Models
by: Wang, Zihan, et al.
Published: (2025)