VLM Robustness

VLM: Vision-Language Model

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26 papers in the last four weeks, up 117% on the four weeks before. 0.3% of all new papers.

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MM-IFEval-Pro: A Multilingual and Attack-Resistant Benchmark for Instruction-Following in Vision-Language Models
Sep 4, 2026Changming Xiao, Zhenliang Ni, Jinhui He +2VLM Robustness Adversarial Attacks on VLMs
Huawei Technologies Ltd. · Beijing, China · Shenzhen, China +1
IchthyoNoma: Nomenclature and Context Sensitivity of Zero-Shot Biological Vision--Language Models for Bangladeshi Freshwater Fish Recognition
Sep 3, 2026Nazim-E-Alam, Tarek Rahman, Md Kishor MorolVLM Robustness Prompt Sensitivity
American International University Bangladesh · United International University · ELITE Research Lab, Queens, New York, USA
DESA-TTA: Dynamic EMA and Source Anchoring for Test-Time Adaptation
Sep 1, 2026Atif Belal, Lilian Hollard, Marco Pedersoli +1Open-Vocabulary Object Detection VLM Robustness
LIVIA, ILLS, Dept. of Systems Engineering, ETS Montréal, Canada
Reliability Challenges in Diffusion Vision-Language Models
Sep 1, 2026Md. Atabuzzaman, Chris ThomasVLM Evaluation VLM Robustness
Department of Computer Science Virginia Tech
Partition-Aware Unlearning for Removing Spurious Correlations in Large Vision-Language Models
Aug 30, 2026Aditi Sarker, Nazreen Shah, Rafi Ibn Sultan +3VLM Evaluation VLM Unlearning
Department of Computer Science, Wayne State University, MI, USA · Department of Electronics & Communications Engineering, IIIT Delhi, India · Institute for AI and Data Science (AIDaS), Wayne State University, MI, USA
Hallucination Mitigation for Large Vision-Language Models via Implicit Feature Stabilization
Aug 30, 2026Aditi Sarker, Rafi Ibn Sultan, Hui Zhu +2VLM Robustness Vision-Language Models
Department of Computer Science, Wayne State University, MI, USA · Institute for AI and Data Science (AIDaS), Wayne State University, MI, USA
Fully Unleashing the Multimodal Attacker: Meta-Adaptive Jailbreaking of Vision-Language Models
Aug 27, 2026Benlei Cui, Shen Pang, Yuke Wang +7VLM Robustness Adversarial Attacks on VLMs
1Yuvion Team, Alibaba Group · Laboratory for Statistical Monitoring and Intelligent Governance of Common Prosperity, School of Statistics and Data Science, Zhejiang Gongshang University
MVC-Bench: Benchmarking Calibration of Medical Vision-Language Models
Aug 27, 2026Ashshak Sharifdeen, Shihab Aaqil Ahamed, Ufaq Khan +6VLM Evaluation VLM Robustness
1Mohamed bin Zayed University of AI · 2Sabaragamuwa University of Sri Lanka · 3Digital Platform Development, SLT PLC
How Do VLMs Behave When Blind or Misled? Behavioral Evaluation of VLMs on Scientific Figures
Aug 13, 2026Paul Osemudiame Oamen, Owusu-Banahene Osei, Ananya Mukherjee +4VLM Evaluation VLM Robustness
The Aberdeen NLP Research Group, University of Aberdeen, UK · International Institute of Information Technology Hyderabad, India · University of Technology Nuremberg, Germany +1
QuISE: Defense against Typographic Attacks on VLMs via Query-Irrelevant Semantic Editing
Aug 13, 2026Shubin Lu, Jiaqi Yin, Yihao HuangVLM Robustness Adversarial Attacks on VLMs
School of Software, Northwestern Polytechnical University, Xi’an, China · Software Engineering Institute, East China Normal University, Shanghai, China
NullEdit: Stealthy Image Protection via VLM Condition Redirection
Aug 11, 2026Weiyao Huang, Liqin Wang, Ziqi Sheng +1VLM Robustness Representation Steering
School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou, China
SafeCap: Improving LVLM Safety with Image Captioning Reinforcement Learning
Aug 11, 2026Caoyuan Ma, Wenpu Liu, Weichu Xie +12VLM Robustness Adversarial Attacks on VLMs
The University of Tokyo · Peking University · Wuhan University +4
Explore, Map, Remember, Decide: Are Embodied VLMs Ready for Safety-Critical Scenarios?
Aug 8, 2026Gabriele La Malfa, Nitay Alon, Emanuele La Malfa +2VLM Evaluation Memory-Augmented VLMs
King’s College London, UK · Massachusetts Institute of Technology, USA · University of Oxford, UK +2
BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning
Aug 7, 2026Saim Rehman, Muhammad ShafiqueVLM Evaluation VLM Robustness
eBRAIN Lab New York University Abu Dhabi (NYUAD) Abu Dhabi, United Arab Emirates
SABRE: Scalable and Automated Benchmarking of VLMs under Stress
Aug 7, 2026Zixuan Lan, Luzhe Sun, Matthew R. Walter +1VLM Evaluation VLM Robustness
University of Chicago · Stony Brook University · Toyota Technological Institute at Chicago
Vision-Language Model Confidence Is Not a Property of the Answer
Aug 6, 2026Reza Khanmohammadi, Erfan Miahi, Ivan Brugere +4VLM Robustness Adversarial Attacks on VLMs
Michigan State University · JPMorgan AI Research · Henry Ford Health
Hijacking Robots with a Piece of Paper: A Systematic Study of Physical Prompt Injection in VLM-Controlled Robots
Aug 6, 2026S. M . Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, W. K. R. Sachinthana +1VLM Robustness Adversarial Attacks on VLMs
Engineering Product Development Pillar · Singapore University of Technology and Design · Somapah Rd, Singapore 487372
Evaluating the Diagnostic Robustness of Vision-Language Models Under Visual and Textual Perturbations
Aug 5, 2026Ali Khoramfar, Mohammad Javad Dousti, Alireza Mohamadian +1VLM Evaluation VLM Robustness
Department of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran · Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Tehran University of Medical Sciences, Tehran, Iran
CARGO-VL: Counterfactual Arbitration with Risk-Constrained Group Optimization for Vision-Language Models
Aug 5, 2026De Jiang, Zhengyang Zhang, Kehong Yuan +1VLM Robustness Counterfactual Evaluation of VLMs
SIGNPOST-Bench: Benchmarking Text-Vision Conflict Resolution in Multimodal Large Language Models
Aug 4, 2026Sirun Li, Minghao Liu, Ling Dai +4VLM Robustness Multimodal Large Language Models
Peking University, Beijing, China · 22077AI · The Hong Kong University of Science and Technology, Hong Kong, China
In-Context Collapse in Vision-Language Models and How to Mitigate it?
Aug 3, 2026Mohammad RostamiVLM Robustness Vision-Language Models
Amazon Generative AI Innovation Center∗, USA.
Local Margin Restoration for Test-Time Adaptation of Vision-Language Models
Aug 3, 2026Yan Huang, Guowei Wang, Xu Wang +2VLM Robustness Test-Time Adaptation
Guangzhou University Guangzhou, China · The Second Affiliated Hospital of Guangzhou University of Chinese Medicine Guangzhou, China · Jinan University Zhuhai, China +1
Two Sides of the Same Coin: Co-Evolving Search for Cross-Task Attacks on Vision-Language Models
Aug 3, 2026Xuanhui Lin, Junhao Dong, Mingrong Gong +3VLM Robustness Adversarial Attacks on VLMs
College of Computing and Data Science, Nanyang Technological University, Singapore
HAFI-VLM: A Frequency Perspective for Diagnosing and Enhancing Visual Perception in Vision-Language Models
Aug 3, 2026Jin Cui, Chuanchang Su, Jiayi Lu +3Visual Question Answering VLM Robustness
1State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University · School of Computer Science and Technology, Xi’an Jiaotong University · School of Software Engineering, Xi’an Jiaotong University
Mitigating Visual Degradation in MLLMs via Spatial-Spectral Visual Anchor Learning
Aug 3, 2026Qianlong Yang, Bowen Ye, Xianda Guo +4VLM Robustness Multimodal Large Language Models
China University of Petroleum (East China) Qingdao, Shandong, China · Great Wall Motor · Shanghai Jiao Tong University Shanghai, China +3
ReACT-CLIP: Response-Aware Test-Time Defense for Vision--Language Models
Aug 2, 2026Hashmat Shadab Malik, Toluwani Aremu, Samuele Poppi +2VLM Robustness Adversarial Attacks on VLMs
Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), UAE · Khalifa University, UAE · University of Western Australia, Australia +1
Decoy Images Amplify Caption-Mediated Defenses Against Encoded Jailbreaks
Aug 2, 2026Haoyu Zhang, Xiangchen Guan, Shibo Zheng +2VLM Robustness Adversarial Attacks on VLMs
Learning to See Locally and Align Clinically with Pathology Semantics for Radiology Report Generation
Jul 31, 2026Xuan Cuong NgoRadiology Report Generation VLM Robustness
QR-Structured Thermal Triggers for Targeted Semantic Attacks on Infrared Vision-Language Models
Jul 31, 2026Xiang Chen, Yingying Zhao, Chao Li +7VLM Robustness Adversarial Attacks on VLMs
Scaling Vision-Language Models Is Not Enough to Mitigate Bias
Jul 30, 2026Ioannis Sarridis, Ioannis Kompatsiaris, Symeon PapadopoulosVLM Evaluation VLM Robustness
Information Technologies Institute, CERTH Thessaloniki, Greece

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MM-IFEval-Pro: A Multilingual and Attack-Resistant Benchmark for Instruction-Following in Vision-Language Models

Changming Xiao, Zhenliang Ni, Jinhui He, Han Shu+1

Huawei Technologies Ltd. · Beijing, China · Shenzhen, China+1

VLM Robustness Adversarial Attacks on VLMs Multilingual VLM Evaluation Multimodal Model Evaluation Multimodal Instruction Tuning

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As vision-language models (VLMs) rapidly advance in image understanding, cross-modal reasoning, and complex instruction execution, instruction-following capability has become a key indicator of their reliability and practicality. However, existing multimodal instruction-following benchmarks still suffer from limited language coverage and insufficient adversarial safety scenarios, making them inadequate for evaluating real-world multilingual and safety-sensitive settings. To address these gaps, we present MM-IFEval-Pro, a multimodal instruction-following benchmark covering Chinese and English tasks as well as diverse instruction hijacking cases. MM-IFEval-Pro includes 4 major task categories and 24 subcategories and 8 instruction categories with 52 subcategories, with each sample containing an average of 3.0 constraints to realistically simulate complex instruction scenarios. We further construct a reinforcement-learning training set enriched with Chinese and adversarial instructions, which significantly improves model performance on MM-IFEval-Pro and transfers effectively to other mainstream multimodal benchmarks, demonstrating strong cross-task and cross-language generalization.

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