MLLM Safety

MLLM: Multimodal Large Language Model

Latest papers

27 papers5 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

When Reasoning Is Not Enough: Proactive Inquiry for Cross-Modal Safety in Multimodal Large Language Models
Oct 15, 2026Wei Cai, Jian Zhao, Yuchen Yuan +1Multimodal Multi-Turn Safety Alignment VLM Safety
Institute of Artificial Intelligence (TeleAI), China Telecom, P. R. China. · Peking University. · School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, P. R. China.
Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs
Oct 8, 2026Tongxi Wu, Yuyang Cheng, Jiacheng Xian +5MLLM Safety Adversarial Attacks on VLMs
Nanjing University · The Hong Kong University of Science and Technology (Guangzhou) · Independent Researcher +2
Reading, Not Manipulating: Leveraging Router Logits for Multimodal Safety in MoE Vision-Language Models
Oct 6, 2026Ziyuan Yang, Wenxuan Ding, Shangbin Feng +1Vision-Language Models Safety Filtering
University of Washington · New York University
MLLMs Fail to Refuse when Using Tools Agentically
Oct 2, 2026Rikiya Takehi, Ryo Hachiuma, Shaona Ghosh +3MLLM Safety LLM Agent Safety
MIT · NVIDIA
ThinkingGuard: Decoding Implicit Hazards via Step-by-Step Risk Attribution in Multimodal Large Language Models
Sep 29, 2026Ruochen Zhang, Yao Huang, Yitong Sun +5Multimodal Reasoning LLM Safety
Beihang University Beijing, China · Tsinghua University Beijing, China · Institute of Artificial Intelligence Beihang University Beijing, China State Key Laboratory of AI Safety
Nemotron 3.5 Content Safety Moderator: A Compact Multimodal, Multilingual, and Reasoning Enabled Content Safety Moderator
Aug 27, 2026Varun Singh, Anuj Doshi, Makesh Narsimhan Sreedhar +2Multimodal Content Moderation LLM Guardrails
NVIDIA Santa Clara, CA
ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models
Aug 21, 2026Wenzheng Jiang, Xuankun Rong, Yuanzhao Zhai +2MLLM Safety LLM Safety Alignment
College of Computer Science and Technology, National University of Defense Technology · State Key Laboratory of Complex & Critical Software Environment · School of Computer Science, Wuhan University
COMIC: Reference-Aware Safety Gating for Multimodal Large Language Models
Aug 18, 2026Md Abdullahil Oaphy, Anhao Xiang, Zongxing Xie +3MLLM Safety LLM Safety
Kennesaw State University, Kennesaw, GA, USA
Exploring and Bridging Knowledge Holes in Unlearned Multimodal Large Language Models
Aug 3, 2026Junxiang You, Junkai Chen, Yuhao He +3Multimodal Large Language Models MLLM Unlearning
University of Chinese Academy of Sciences · Institute of Automation, Chinese Academy of Sciences · 3Cloudspace Technology
Shieldstral
Jul 28, 2026Antonia Calvi, Avinash Sooriyarachchi, Giada Pistilli +273Language Model Safety Evaluation Content Moderation
Evolving Safety Landscape of Multi-modal Large Language Models: A Survey of Emerging Threats and Safeguards
Jul 27, 2026Xi Li, Shu Zhao, Xiaohan Zou +6MLLM Safety Adversarial Attacks on VLMs
University of Alabama at Birmingham · NVIDIA · Penn State University +4
Harnessing Textual Refusal Directions for Multimodal Safety
Jun 30, 2026Moreno D'Incà, Nicu Sebe, Massimiliano ManciniLanguage Model Safety Evaluation Multimodal Large Language Models
University of Trento
SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning
Jun 22, 2026SingGuard TeamLanguage Model Safety Evaluation LLM Guardrails
1AI Security Lab, Ant Group
Safe responses matter: Output-aware safety guardrail mitigate over-refusal in MLLMs
Jun 20, 2026Jiayi Li, Kun ZhanRefusal Behavior in Language Models LLM Guardrails
Lanzhou University
Exploring Adversarial Robustness and Safety Alignment in Multilingual Multi-Modal Large Language Models
Jun 2, 2026Hashmat Shadab Malik, Muzammal Naseer, Salman KhanMLLM Safety Multilingual Language Model Evaluation
Mohamed Bin Zayed University of AI, UAE · Khalifa University, UAE · Australian National University, Australia
Investigating and Alleviating Harm Amplification in LLM Interactions
Jun 1, 2026Ruohao Guo, Wei Xu, Alan RitterMLLM Safety Language Model Safety Evaluation
Georgia Institute of Technology
GuardAD: Safeguarding Autonomous Driving MLLMs via Markovian Safety Logic
May 11, 2026Tianyuan Zhang, Peng Yue, Zihao Peng +8MLLM Safety Autonomous Driving
Beihang University · Zhongguancun Laboratory · Peking University
SafetyALFRED: Evaluating Safety-Conscious Planning of Multimodal Large Language Models
Apr 21, 2026Josue Torres-Fonseca, Naihao Deng, Yinpei Dai +5Safety Evaluation of VLA Models LLM Safety Benchmarks
University of Michigan · Boise State University
Dictionary-Aligned Concept Control for Safeguarding Multimodal LLMs
Apr 10, 2026Jinqi Luo, Jinyu Yang, Tal Neiman +5MLLM Safety Multimodal Large Language Models
University of Pennsylvania · Amazon · University of Central Florida
CASA: Classification Augmented with Safety Attention for Robust Multimodal Alignment
Mar 31, 2026Anurag Kumar, Raghuveer Peri, Jon Burnsky +4MLLM Safety LLM Safety Alignment
The Ohio State University · AWS
When Understanding Becomes a Risk: Authenticity and Safety Risks in the Emerging Image Generation Paradigm
Mar 25, 2026Ye Leng, Junjie Chu, Mingjie Li +5MLLM Safety Image Generation
CISPA Helmholtz Center for Information Security · Xi’an Jiaotong University · Flexera
Structured Visual Narratives Undermine Safety Alignment in Multimodal Large Language Models
Mar 23, 2026Rui Yang Tan, Yujia Hu, Roy Ka-Wei LeeMLLM Safety Adversarial Attacks on VLMs
Singapore University of Technology and Design. · University of British Colombia.
OOD-MMSafe: Advancing MLLM Safety from Harmful Intent to Hidden Consequences
Mar 10, 2026Ming Wen, Kun Yang, Jingyu Zhang +4MLLM Safety LLM Safety
Fudan University, Shanghai, China · Shanghai Innovation Institute, Shanghai, China · Ant Group, Hangzhou, China +1
SaFeR-ToolKit: Structured Reasoning via Virtual Tool Calling for Multimodal Safety
Mar 3, 2026Zixuan Xu, Tiancheng He, Huahui Yi +7Cultural Safety Evaluation of VLMs VLM Safety
Huazhong University of Science and Technology · Beijing University of Posts and Telecommunications · West China Hospital, Sichuan University +1
MUSE: A Run-Centric Platform for Multimodal Unified Safety Evaluation of Large Language Models
Mar 3, 2026Zhongxi Wang, Yueqian Lin, Jingyang Zhang +3Multimodal Large Language Models Multi-Turn Jailbreak Attacks
1Duke University · 2Virtue AI
Towards Multi-modal Multi-turn Safety: From Agentic Interaction to Strategic Alignment
Jan 8, 2026Han Zhu, Jiale Chen, Chengkun Cai +8Language Model Safety Evaluation Multimodal Large Language Models
Hong Kong University of Science and Technology · University College London · AISpeech +1
SGM: Safety Glasses for Multimodal Large Language Models via Neuron-Level Detoxification
Dec 17, 2025Hongbo Wang, AprilPyone MaungMaung, Isao EchizenMLLM Safety Multimodal Robustness
1Graduate School of Information Science and Technology, The University of Tokyo, Japan · 2Information and Society Research Division, National Institute of Informatics, Japan · 3The Graduate University for Advanced Studies, SOKENDAI, Japan

Oct 15, 2026J/K move · Enter open · S save

When Reasoning Is Not Enough: Proactive Inquiry for Cross-Modal Safety in Multimodal Large Language Models

Wei Cai, Jian Zhao, Yuchen Yuan, Xuelong Li

Institute of Artificial Intelligence (TeleAI), China Telecom, P. R. China. · Peking University. · School of Artificial Intelligence, OPtics and ElectroNics (iOPEN), Northwestern Polytechnical University, Xi’an 710072, P. R. China.

Multimodal Multi-Turn Safety Alignment VLM Safety LLM Safety MLLM Safety Multimodal Large Language Models Clarification Question Generation+1

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Multimodal large language models (MLLMs) can act unsafely when individually benign images and texts are interpreted jointly. Beyond implicit reasoning risk, where reasoning drifts toward harm, we identify intent-level risk, where cross-modal ambiguity silently commits the model to a hazardous premise that path-level optimization alone cannot correct. We propose SAFE-PRO, which uses a Risk-Conditioned Uncertainty (RCU) signal, combining predictive entropy with a learned cross-modal risk score, to decide when to ask safety-grounded clarifying questions and where to apply path optimization, under a reward that prioritizes safety and penalizes over-refusal. We also build SSUI-Dialog, a multimodal multi-turn dataset with dual-intent supervision, and theoretically analyze gradient variance and unsafe-completion risk under RCU. Across seven benchmarks and two base MLLMs, SAFE-PRO consistently improves safety over SRPO, roughly halves its over-refusal, and surpasses GPT-4o and Claude-3.5-Sonnet in average single-turn safety.