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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Robust Grounding with MLLMs Against Occlusion and Small Objects via Language-Guided Semantic Cues
Apr 27, 2026Beomchan Park, Seongho Kim, Hyunjun Kim +2VLM Robustness LLM Grounding
Integrated Vision Language Lab., KAIST, Republic of Korea
From Global to Local: Rethinking CLIP Feature Aggregation for Person Re-Identification
Apr 24, 2026Aotian Zheng, Winston Sun, Bahaa Alattar +2VLM Robustness Person Re-Identification
Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195 · Applied Physics Laboratory, University of Washington, Seattle, WA 98195
Ramen: Robust Test-Time Adaptation of Vision-Language Models with Active Sample Selection
Apr 23, 2026Wenxuan Bao, Yanjun Zhao, Xiyuan Yang +1VLM Robustness Test-Time Adaptation
University of Illinois Urbana-Champaign
Seeing Isn't Believing: Uncovering Blind Spots in Evaluator Vision-Language Models
Apr 23, 2026Mohammed Safi Ur Rahman Khan, Sanjay Suryanarayanan, Tushar Anand +1VLM Evaluation VLM Robustness
♠Nilekani Centre at AI4Bharat ♢Indian Institute of Technology Madras · ♠Nilekani Centre at AI4Bharat · ♣BITS Pilani, Hyderabad
Latent Denoising Improves Visual Alignment in Large Multimodal Models
Apr 23, 2026Dhruv Parikh, Jacob Fein-Ashley, Rajgopal Kannan +1VLM Robustness Multimodal Large Language Models
University of Southern California Los Angeles, CA, USA · DEVCOM ARL Army Research Office USA
How VLAs (Really) Work In Open-World Environments
Apr 23, 2026Amir Rasouli, Yangzheng Wu, Zhiyuan Li +4VLM Robustness Long-Horizon Robotic Manipulation
Noahs Ark Laboratory, Huawei Technologies Canada. · while at Huawei Canada.
If you're waiting for a sign... that might not be it! Mitigating Trust Boundary Confusion from Visual Injections on Vision-Language Agentic Systems
Apr 21, 2026Jiamin Chang, Minhui Xue, Ruoxi Sun +3VLM Robustness Adversarial Attacks on VLMs
University of New South Wales, Sydney, NSW 2052, Australia · CSIRO’s Data61, Marsfield, NSW 2122, Australia · Macquarie University, NSW 2109, Australia
Hierarchically Robust Zero-shot Vision-language Models
Apr 20, 2026Junhao Dong, Yifei Zhang, Hao Zhu +2Hierarchical Classification VLM Robustness
1Nanyang Technological University · 2CFAR, IHPC, A*STAR · 3Northwest Polytechnical University +2
DUALVISION: RGB-Infrared Multimodal Large Language Models for Robust Visual Reasoning
Apr 20, 2026Abrar Majeedi, Zhiyuan Ruan, Ziyi Zhao +3Cross-Modal Learning Visual Question Answering
University of Wisconsin-Madison · Amazon · Northeastern University
ProtoCLIP: Prototype-Aligned Latent Refinement for Robust Zero-Shot Chest X-Ray Classification
Apr 20, 2026Florian Kittler, Sheethal Bhat, Andreas MaierVLM Robustness Chest X-Ray Classification
Friedrich-Alexander University Erlangen-Nuremberg, Erlangen 91054, Germany
Towards Robust Text-to-Image Person Retrieval: Multi-View Reformulation for Semantic Compensation
Apr 20, 2026Chao Yuan, Yujian Zhao, Haoxuan Xu +1VLM Robustness Vision-Language Retrieval
Beihang University
OFlow: Injecting Object-Aware Temporal Flow Matching for Robust Robotic Manipulation
Apr 20, 2026Kuanning Wang, Ke Fan, Chenhao Qiu +5VLM Robustness Flow Matching
Fudan University Shanghai, China · University of Southern California Los Angeles, CA, USA · KAUST Saudi Arabia
Spatiotemporal Sycophancy: Negation-Based Gaslighting in Video Large Language Models
Apr 20, 2026Ziyao Tang, Pengkun Jiao, Bin Zhu +3VLM Evaluation VLM Robustness
Institute of Trustworthy Embodied AI, Fudan University · Shanghai Key Laboratory of Multimodal Embodied AI · Singapore Management University
When Background Matters: Breaking Medical Vision Language Models by Transferable Attack
Apr 19, 2026Akash Ghosh, Subhadip Baidya, Sriparna Saha +1VLM Robustness Adversarial Attacks on VLMs
Indian Institute of Technology Patna1 · Work done as Visiting Researcher at MBZUAI · MBZUAI3 +1
RemoteShield: Enable Robust Multimodal Large Language Models for Earth Observation
Apr 19, 2026Rui Min, Liang Yao, Shiyu Miao +5Remote Sensing Image Understanding VLM Robustness
1Hohai University · 2Nanjing University · 3Southeast University
Cross-Modal Attention Analysis and Optimization in Vision-Language Models: A Study on Visual Reliability
Apr 19, 2026Lijie ZhouCross-Modal Learning VLM Robustness
School of Computer Science University of Nottingham Ningbo China Ningbo, China
Prompt Sensitivity in Vision-Language Grounding: How Small Changes in Wording Affect Object Detection
Apr 18, 2026Dawar Jyoti Deka, Amit Sethi, Syed Mohammad AliOpen-Vocabulary Object Detection VLM Robustness
Department of Aerospace Engineering, Indian Institute of Technology Bombay, Mumbai, India · Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai, India
SIF: Semantically In-Distribution Fingerprints for Large Vision-Language Models
Apr 18, 2026Yifei Zhao, Qian Lou, Mengxin ZhengVLM Robustness Language Model Fingerprinting
University of Central Florida
Information Router for Mitigating Modality Dominance in Vision-Language Models
Apr 17, 2026Seulgi Kim, Mohit Prabhushankar, Ghassan AlRegibVLM Robustness Vision-Language Models
OLIVES at the Center for Signal and Information Processing CSIP, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
Dual-Modality Anchor-Guided Filtering for Test-time Prompt Tuning
Apr 14, 2026Jungwon Choi, Eunwoo KimVLM Robustness VLM Adaptation
School of Computer Science and Engineering, Chung-Ang University
E-VLA: Event-Augmented Vision-Language-Action Model for Dark and Blurred Scenes
Apr 6, 2026Jiajun Zhai, Hao Shi, Shangwei Guo +2Event-Based Vision VLM Robustness
Zhejiang University · Ant Group · Hunan University
TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios
Mar 31, 2026Qiucheng Yu, Ruijie Xu, Mingang Chen +2VLM Evaluation VLM Robustness
City University of Hong Kong · East China Normal University · Shanghai Development Center of Computer Software Technology +1
Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering
Mar 30, 2026Yanjie Zhang, Yafei Li, Rui Sheng +5VLM Robustness Chart QA
HKUST, Hong Kong SAR, China · HKUST(GZ), Guangzhou, China
Can VLMs Reason Robustly? A Neuro-Symbolic Investigation
Mar 25, 2026Weixin Chen, Antonio Vergari, Han ZhaoVLM Robustness Visual Reasoning
University of Illinois Urbana-Champaign · University of Edinburgh
StageCraft: Execution Aware Mitigation of Distractor and Obstruction Failures in VLA Models
Mar 21, 2026Kartikay Milind Pangaonkar, Prabin Rath, Omkar Patil +1VLM Robustness Robotic Manipulation
Arizona State University
T-QPM: Enabling Temporal Out-Of-Distribution Detection and Domain Generalization for Vision-Language Models in Open-World
Mar 19, 2026Aditi Naiknaware, Salimeh SekehVLM Robustness Domain Generalization
San Diego State University
Visual Prompt Discovery via Semantic Exploration
Mar 17, 2026Jaechang Kim, Yotaro Shimose, Zhao Wang +3VLM Robustness
Sony Group Corporation · Pohang University of Science and Technology · National Yang Ming Chiao Tung University
Are Video Reasoning Models Ready to Go Outside?
Mar 11, 2026Yangfan He, Changgyu Boo, Jaehong YoonVLM Robustness Video Reasoning
NTU Singapore · Korea University
ProtoDCS: Towards Robust and Efficient Open-Set Test-Time Adaptation for Vision-Language Models
Feb 27, 2026Wei Luo, Yangfan Ou, Jin Deng +4VLM Robustness Test-Time Adaptation
South China Agricultural University · Pazhou Laboratory · South China University of Technology +1
When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs
Feb 19, 2026Yu Fang, Yuchun Feng, Dong Jing +5VLM Robustness Counterfactual Evaluation of VLMs
University of North Carolina at Chapel Hill

Apr 27, 2026, cs.CVJ/K move · Enter open · S save

Robust Grounding with MLLMs Against Occlusion and Small Objects via Language-Guided Semantic Cues

Beomchan Park, Seongho Kim, Hyunjun Kim, Sungjune Park+1

Integrated Vision Language Lab., KAIST, Republic of Korea

VLM Robustness LLM Grounding Vision-Language Grounding

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While Multimodal Large Language Models (MLLMs) have enhanced grounding capabilities in general scenes, their robustness in crowded scenes remains underexplored. Crowded scenes entail visual challenges (i.e., occlusion and small objects), which impair object semantics and degrade grounding performance. In contrast, language expressions are immune to such degradation and preserve object semantics. In light of these observations, we propose a novel method that overcomes such constraints by leveraging Language-Guided Semantic Cues (LGSCs). Specifically, our approach introduces a Semantic Cue Extractor (SCE) to derive semantic cues of objects from the visual pipeline of an MLLM. We then guide these cues using corresponding text embeddings to produce LGSCs as linguistic semantic priors. Subsequently, they are reintegrated into the original visual pipeline to refine object semantics. Extensive experiments and analyses demonstrate that incorporating LGSCs into an MLLM effectively improves grounding accuracy in crowded scenes.

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Latest papers 295