Vision-Language Models for Vision Tasks: A Survey

Deep Residual Learning for Image Recognition

He, K., Zhang, X., Ren, S., & Sun, J. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.90 · Cited by 235,474

Random Forests

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Attention Is All You Need

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Very Deep Convolutional Networks for Large-Scale Image Recognition

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ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2018) · arXiv · doi:10.48550/arxiv.1810.04805 · Cited by 73,173

Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks

Ren, S., He, K., Girshick, R., & Sun, J. (2015) · arXiv · doi:10.48550/arxiv.1506.01497 · Cited by 70,812

ImageNet: A large-scale hierarchical image database

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Support-vector networks

Cortes, C., & Vapnik, V. (1995) · Machine Learning · doi:10.1007/bf00994018 · Cited by 59,421

Video-Based Traffic Anomaly Detection with Vision-Language Models: A Survey

Zheng, Y., Zhou, W., Nastić, S., & Wang, C. (2025) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc60802.2025.11423492 · Cited by 1

Composite-Semantic Control for NEV Styling Using Bayesian Evidence Updating and LoRA-Tuned Diffusion Models

Kuang, Y., He, X., Liu, F., Liu, Y., & Song, N. (2026) · IEEE Access · doi:10.1109/access.2026.3685439 · Cited by 1

Enhancing Vision Language Corruption Robustness using Cross-Distribution & Prompted Denoisers

Latif, S. S., Shiper, S., Kiran, K. M. R., Ishmam, M. F., Hossain, M. A., Kamal, A. R. M., & Ashmafee, M. H. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00558 · Cited by 1

Applications of Intelligent Image Recognition Technology in Modern Security Inspection and the Evolution of Screening Equipment

Shen, X., & Yang, G. (2026) · International Conference on Generative Artificial Intelligence and Information Security (GAIIS) · doi:10.1109/gaiis69281.2026.11519280 · Cited by 1

Exploring Vision-Language Models for Weakly Supervised Video Anomaly Detection: Experiments and Analysis

Saket, O., Aicha, A. B., & Fathallah, H. (2026) · IEEE Middle East and North Africa Communications Conference (MENACOMM) · doi:10.1109/menacomm69507.2026.11532827 · Cited by 1

A multimodal vision–language framework using contrastive language-image pre-training for robust facial expression analysis in realistic classroom environments

Ayub, N., Alam, F., Ullah, A., Ahmad, J., Farman, H., Shafai, W. E., & Sedik, A. (2026) · Journal of King Saud University - Computer and Information Sciences · doi:10.1007/s44443-026-00905-1 · Cited by 1

Cascade context-oriented spatio-temporal attention network for efficient and fine-grained video-grounded dialogues

Wang, H., Guo, B., Chen, M., Zhang, Q., Ding, Y., Zhang, Y., & Yu, Z. (2024) · Frontiers of Computer Science · doi:10.1007/s11704-024-40387-w · Cited by 1

I2OL-Net: Intra-Inter Objectness Learning Network for Point-Supervised X-Ray Prohibited Item Detection

Wang, C., Yan, Y., Xue, J., & Wang, H. (2025) · IEEE Transactions on Information Forensics and Security · doi:10.1109/tifs.2025.3550052 · Cited by 2

A Digital Twin Framework for Robot Grasp and Motion Generation

Dong, J., Jia, Z., Wang, Y., & Ren, L. (2024) · IEEE Smart World Congress (SWC) · doi:10.1109/swc62898.2024.00314 · Cited by 1

LViTES: Leveraging Vision and Text for Enhancing Segmentation of Endoscopic Images

La, T., Tran, M.-H., Dao, H. V., & Tran, T.-H. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-2644-1_12 · Cited by 1

LLaVA-MultiMammo: adapting vision-language models for explainable and comprehensive multiview mammogram analysis in breast cancer assessment

Chen, X., Chen, J., Chen, X., Gichoya, J. W., Trivedi, H., & Yang, X. (2025) · SPIE Medical Imaging: Computer-Aided Diagnosis · doi:10.1117/12.3049085 · Cited by 1

Combining AI and Crowdsourcing to Identify Misinformation in Online News

Besheli, M. A., & Jasim, M. (2025) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3706599.3720007 · Cited by 1

A multimodal automatic generation and annotation framework for prohibited and restricted goods in online transactions

Liu, W., Zhang, S., Liu, H., & Zou, J. (2025) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2025.111000 · Cited by 1

T-GET3D: A Generative Model of High-Quality 3D Textured Shapes Guided by Texts

Shi, X., Lin, Y., Cheng, X., Zhang, P., Yang, D., & Zhang, L. (2025) · Lecture notes in computer science · doi:10.1007/978-981-96-6579-2_9 · Cited by 1

Open-World 3D Scene Understanding with Cross-Modal Dual Consistency Learning

Han, X.-F., Wang, C., Wang, Y., & Wang, M. (2025) · International Conference on Multimedia Retrieval · doi:10.1145/3731715.3733408 · Cited by 1

Explorando o uso de VLMs para classificação Zero-Shot de Imagens

Figueiredo, C. M. S., & de Melo, T. E. (2025) · doi:10.5753/sbcup.2025.7136 · Cited by 1

Adaptive Ternary Division with VLM Knowledge for Domain Adaptation of Black-Box Predictors

Zeng, Z., Zhang, Y., & Wang, J. (2025) · Communications in computer and information science · doi:10.1007/978-981-96-9986-5_41 · Cited by 1

GanitBench: A bi-lingual benchmark for evaluating mathematical reasoning in Vision Language Models

Bandooni, A., & Subburaj, B. (2025) · International Conference on Recent Advances in Information Technology · doi:10.1109/rait65068.2025.11089442 · Cited by 1

Logical Anomaly Detection with Text-based Logic via Component-Aware Contrastive Language-Image Training

Lee, S.-E., Kim, S., An, S., Lee, S.-C., & Park, S. H. (2025) · ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) · doi:10.1145/3711896.3737032 · Cited by 1

Text-guided visual prompt learning with semantic prompt generation and feature fusion

Zhang, J., & Wang, S. (2025) · Neurocomputing · doi:10.1016/j.neucom.2025.131253 · Cited by 1

Demobias: an Empirical Study to Trace Demographic Biases in Vision Foundation Models

Sufian, A., Ghosh, A., Barman, D., Leo, M., & Distante, C. (2025) · International Workshop on Biometrics and Forensics (IWBF) · doi:10.1109/iwbf63717.2025.11113455 · Cited by 1

Confidence Calibration in Contrastive Vision-Language Models

Wang, S., Zhou, K., & Wei, H. (2025) · Advances in computer vision and pattern recognition · doi:10.1007/978-3-031-94969-2_9 · Cited by 1

AMA: Adaptive Multimodal Adversarial Attack with Dynamic Perturbation Optimization

Shi, Y., He, Z., Jin, T., Tong, H., & Fu, Z. (2025) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2025.067658 · Cited by 1

JDA-attack: leveraging joint multimodal data augmentation to enhance adversarial transferability of vision-language pre-training models

Ren, X., Zhang, C., Han, G., Chen, B., & Fan, Z. (2025) · Complex & Intelligent Systems · doi:10.1007/s40747-025-02036-y · Cited by 1

Leveraging Generalist VQA Models to Improve Zero-Shot Pedestrian Attribute Recognition

Salas-Cáceres, J. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-04968-1_2 · Cited by 1

CARP: cloud-adaptive robust prompting of vision-language models for ship classification under cloud occlusion

Zhan, H., Song, Y., Huang, X., Tan, X. J., & Zhang, T. (2025) · Frontiers in Remote Sensing · doi:10.3389/frsen.2025.1662024 · Cited by 1

Scaling down, Powering up: A Survey on the Advancements of Small Vision-Language Models

Ahmed, S. I., Hasan, M. Z., Niloy, A. J., Monsur, S. M., & Albert, M. V. (2025) · Information Fusion · doi:10.1016/j.inffus.2025.103805 · Cited by 1

LLM-TTA: Leveraging Large Language Models for Test-Time Adaptation in Image Quality Assessment

Bashir, A., Kumar, R., Jakhetiya, V., Subudhi, B. N., Jaiswal, S. P., & Lin, W. (2025) · International Workshop on Multimedia Content Generation and Evaluation: New Methods and Practice (McGE) · doi:10.1145/3746278.3759394 · Cited by 1

Generating Robotic Control Strategies With LLMs : Via Human–Robot Voice Interaction

Wang, X., Zhou, G., Hua, H., Tang, Z., & Cao, Y. (2025) · Concurrency and Computation Practice and Experience · doi:10.1002/cpe.70372 · Cited by 1

Cross-Modal Prototype Augmentation and Dual-Grained Prompt Learning for Social Media Popularity Prediction

Zhou, A., Tu, M., Wang, L., Sun, T., Cheng, Z., Yin, Y., Jiang, Z., & Gu, Q. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3763784 · Cited by 1

Cross-Domain Attribute Alignment with CLIP: A Rehearsal-Free Approach for Class-Incremental Unsupervised Domain Adaptation

Mi, K., Kang, G., Li, G., Zhao, L., Zhou, T., & Gong, C. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755184 · Cited by 1

OV-VOD: Open-Vocabulary Video Object Detection

Zheng, Z., Cao, Y., Gao, J., & Wang, H. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3755402 · Cited by 1

Hierarchical Vision-Language Reasoning for Multimodal Multiple-Choice Question Answering

Zhou, A., Gu, Z., Sun, T., Chen, J., Tu, M., Cheng, Z., Yin, Y., Jiang, Z., & Gu, Q. (2025) · ACM International Conference on Multimedia (ACM MM) · doi:10.1145/3746027.3761997 · Cited by 1

DAPL: Integration of Positive and Negative Descriptions in Text-Based Person Search

Deng, Y., Hu, Z., Xin, Z., Deng, C., & Zhao, Q. (2025) · IEEE International Conference on Multimedia and Expo (ICME) · doi:10.1109/icme59968.2025.11210038 · Cited by 1

Efficient Few‐Shot Learning in Remote Sensing: Fusing Vision and Vision‐Language Models

Chua, J. Y., Zolotas, A. C., & Arana‐Catania, M. (2025) · Applied AI Letters · doi:10.1002/ail2.70010 · Cited by 1

Dual Alignment-Enhanced Fashion Vision-Language Pre-Training

Guan, W., Wang, K., Song, X., Zhang, K., Chang, X., & Zhang, S. (2025) · ACM Transactions on Multimedia Computing Communications and Applications · doi:10.1145/3774884 · Cited by 1

KIEPrompter: Leveraging Lightweight Models' Predictions for Cost-Effective Key Information Extraction using Vision LLMs

Vaiani, L., Ding, Y., Cagliero, L., Lee, J., Garza, P., Poon, J., & Han, S. C. (2025) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3746252.3761416 · Cited by 1

TDAdv: Improving Transferability of Unrestricted Adversarial Examples with Text-Guided Diffusion

Zhao, S., Hu, S., Liang, Z., Huang, S., & Peng, A. (2025) · Communications in computer and information science · doi:10.1007/978-981-95-4109-6_5 · Cited by 1

Improving accountability and explainability in robots through encryption, large language models, and visual language models

Fernández-Becerra, L., Sobrín-Hidalgo, D., González-Santamarta, M. Á., Guerrero‐Higueras, Á. M., Rodríguez-Lera, F. J., & Olivera, V. M. (2025) · Logic Journal of IGPL · doi:10.1093/jigpal/jzaf016 · Cited by 1

Text-Guided Sports Highlights: A CLIP-Based Framework for Automatic Video Summarization

Rodrigo, M., Cuevas, C., & Garcia, N. N. (2025) · IEEE Access · doi:10.1109/access.2025.3643500 · Cited by 1

Visualizing Radiologic Connections: An Explainable Coarse-to-Fine Foundation Model with Multiview Mammograms and Associated Reports

Gao, Y., Zhou, H.-Y., Wang, X., Portaluri, A., Zhang, T., Beets‐Tan, R. G. H., Han, L., Lu, C., Estacio, L., D'Angelo, A. R., et al. (2025) · Radiology Artificial Intelligence · doi:10.1148/ryai.240646 · Cited by 1

Unlocking the potential of ChatGPT in investigating NDVI over the vineyard habitat of the Mediterranean coastal city

Hwang, Y.-S., Schlüter, S., Lee, J.-J., & Um, J. (2025) · Journal of Coastal Conservation · doi:10.1007/s11852-025-01184-0 · Cited by 1

Multimodal hierarchical classification using cascade-of-thought

Hou, J., Tan, Z., Hu, Q., Wang, P., & Gong, Y. (2025) · Information Processing & Management · doi:10.1016/j.ipm.2025.104555 · Cited by 1

SPARTA: Spectral Prompt Agnostic Adversarial Attack on Medical Vision-Language Models

Hanif, A., Zaheer, Z., Khan, S., Khan, F. S., & Anwer, R. M. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-06593-3_7 · Cited by 1

Segment Anything for Breast Cancer Ultrasound Image

Huang, J., Zhang, Y., Xie, Y., Deng, J., Wang, D., Mei, L., & Lei, C. (2025) · Signal Image and Video Processing · doi:10.1007/s11760-025-05032-4 · Cited by 1

A multilevel fine-grained feature fusion method for cross-modal image–text retrieval

Wu, B., Fang, H., Shao, Z., Kang, L., Xu, G., Wang, T., & Guan, Y. (2025) · Discover Computing · doi:10.1007/s10791-025-09871-0 · Cited by 1

Nova: Real-Time Agentic Vision-Language Model Serving With Adaptive Cross-Stage Parallelization

Xu, Y., Liu, S., Zhang, D., Yan, B., Wu, F., & Chen, G. (2025) · IEEE Real-Time Systems Symposium (RTSS) · doi:10.1109/rtss66672.2025.00038 · Cited by 2

Robust defense strategies for multimodal contrastive learning: efficient fine-tuning against backdoor attacks

Hossain, M. I., Sajeeda, A., Perla, N. K., & Shao, M. (2026) · Multimedia Tools and Applications · doi:10.1007/s11042-026-21339-x · Cited by 1

Genetic Algorithm for Interpretability in Vision Language Models

Barreto, M. H. L., Oliveira, C. L., Santos, F. A. O., Nováis, P., Matos, L. N., & Britto, A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-15987-8_40 · Cited by 1

Automating Classroom Observation: AI-Enabled Behavior Monitoring for Adaptive Educational Management

Zhu, S., Fang, Q., Zheng, R., & Zhu, D. Z. (2025) · International Conference on Artificial Intelligence and Future Education (AIFE) · doi:10.1145/3785987.3786101 · Cited by 1

Feature-Aligned Cell Detection for Heterogeneous Microscopic Images With Focal Attenuated Distance Transform

Liu, R., Wu, C., Zhang, Y., Song, H., Yuan, F., Dai, W., Li, W. J., & Liu, J. (2026) · IEEE Transactions on Automation Science and Engineering · doi:10.1109/tase.2026.3661872 · Cited by 1

Can Vision-Language Models Understand Construction Workers? An Exploratory Study

Bui, H., Chodosh, N., & Tavakoli, A. (2026) · IEEE Access · doi:10.1109/access.2026.3661520 · Cited by 2

DESIGN OF AN AUTOMATIC CONTROL AND NAVIGATION SYSTEM FOR UAVs WITH COMPUTER-VISION-BASED CORRECTION

Ushkarenko, O. O., Сергійович, Д. О., Обрубов, А. В., Sirivchuk, A. S., & Bilyuk, I. (2025) · Scientific Bulletin Kherson State Maritime Academy · doi:10.33815/2313-4763.2025.2.31.077-089 · Cited by 1

CatAID: Category-Guided AI-Generated Image Detection via Vision-Language Model Adaptation

Cai, Y., Jia, S., Tian, J., Dai, J., Han, J., & Lyu, S. (2025) · IEEE International Conference on Computer Vision Workshops · doi:10.1109/iccvw69036.2025.00166 · Cited by 1

Review of generative AI for lesion localization and automatic report generation

Sun, K., Wang, Y., Huang, S., Liu, Y., Chen, H., Lian, Z., Tan, M., Lin, X., Zhou, W., Qiu, Z., et al. (2026) · Med-X · doi:10.1007/s44258-026-00076-8 · Cited by 1

Investigating the Viability of Employing Multi-modal Large Language Models in the Context of Audio Deepfake Detection

Chuchra, A., Reddy, S., Mishra, S., Das, A., & Dhall, A. (2025) · IEEE International Joint Conference on Biometrics (IJCB) · doi:10.1109/ijcb65343.2025.11410761 · Cited by 1

S2SWCLIP: semantic-optimized prompts with spatial-wavelet synergy for zero-shot anomaly detection

Zhang, H., Wu, C., Lu, J., & Jing, M. (2026) · Scientific Reports · doi:10.1038/s41598-026-43044-3 · Cited by 1

C&D-CLIP: Cascaded decoder and deep cross visual prompt tuning for zero-shot semantic segmentation

Li, L., Liang, Y., Wang, Z., Bao, Y., & Yang, S. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.113528 · Cited by 1

A Review of Image Denoising Techniques: Models, Learning Paradigms and Emerging Trends

Kumar, A., Singh, P. K., & Yadav, J. (2026) · International Journal of Science and Technology (IJST) · doi:10.70558/ijst.2026.v3.i1.241201 · Cited by 1

Learn2Fold: Structured Origami Generation with World Model Planning

Huang, Y., Chen, Y., Jiang, Y., Han, J., Tu, Z., Yang, Y., & Jiang, C. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37350-2_3 · Cited by 1

DRIVE: Diagnostic Report Integration via VLM and LLM Explanations for Explainable Vehicle Engine Fault Diagnosis

Lee, J., & Rew, J. (2026) · Computer Modeling in Engineering & Sciences · doi:10.32604/cmes.2026.076888 · Cited by 1

Tokenization and representation learning of contour data using bidirectional encoder representations from transformers (BERT)

Kong, B., Tinghua Ai, A., Dai, Z., Liao, X., Yan, L., Xiao, T., Yang, M. J., & Yu, H. (2026) · International Journal of Geographical Information Systems · doi:10.1080/13658816.2026.2643000 · Cited by 1

UTCAPTCHA: A CAPTCHA Utilizing Unreal Timing in Guided Generative AI-extended Videos

Lin, L., Wang, K., Abdallah, M., & Cai, W. (2026) · International Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV) · doi:10.1145/3798065.3798075 · Cited by 1

RemoteAgent: Bridging Vague Human Intents and Earth Observation With RL-Based Agentic MLLMs

Yao, L. X., Xu, S., Liu, F., Zhang, C., Yao, B., Min, R., Li, Y., Ouyang, C., Di, S., & Zhang, M.-L. (2026) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2026.3724339 · Cited by 11

Towards efficient context-aware classification with compact VLM architectures: indoor fire case study

Giang, A. T., Doan, N. Q., Minh Duong, T. R. A. N., Khanh Dung, T. R. A. N., Nguyen, H. A., & Busson, A. (2026) · Scientific Reports · doi:10.1038/s41598-026-48743-5 · Cited by 1

VL-Grading: A vision–language distillation framework for preoperative grading of clear cell renal cell carcinoma from multi-phase contrast-enhanced ultrasound

Zou, M., Liu, Y., Shang, J., Liu, Y., He, H., Chen, Y., Chen, L., & Zhang, Q. (2026) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2026.110321 · Cited by 1

HMVLA: Hyperbolic Multimodal Fusion for Vision-Language-Action Models

Wang, K. F., Feng, X., Qu, M., & Su, T. (2026) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp55912.2026.11464207 · Cited by 2

Brain-Grasp: Graph-Based Saliency Priors for Improved FMRI-Based Visual Brain Decoding

Moradi, M., Moradi, M., Grassia, M., & Mangioni, G. (2026) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp55912.2026.11464921 · Cited by 1

Geo3DVQA: Evaluating Vision-Language Models for 3D Geospatial Reasoning from Aerial Imagery

Tsujimoto, M., Wang, J., Xuan, W., & Yokoya, N. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00485 · Cited by 1

ITSELF: Attention Guided Fine-Grained Alignment for Vision–Language Retrieval

Nguyen, T.-H., Tran, H.-L., & Ngo, T. D. (2026) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv61042.2026.00147 · Cited by 1

VizArQA: A Foundation for Visual Question Answering in Architectural Simulation

Mehta, M. D., Ezemba, J., Tucker, C., & McComb, C. (2026) · ASME Journal of Engineering for Sustainable Buildings and Cities · doi:10.1115/1.4071865 · Cited by 1

AI-Assisted Discrete Mathematics Teaching Platform Based on Multimodal Learning Resources

Kuang, H., Li, H., Zeng, M., & Wang, J. (2026) · Communications in computer and information science · doi:10.1007/978-981-95-7731-6_9 · Cited by 2

CIM: Interpretable model with consistency representation and prompt learning

Dong, L., Li, Z., Chen, L., Zheng, C., Peng, X., Li, Y., & Cui, X. (2026) · Information Processing & Management · doi:10.1016/j.ipm.2026.104881 · Cited by 1

Concept-Enhanced Multimodal RAG: Towards Interpretable and Accurate Radiology Report Generation

Salmè, M., Siciliano, F., Silvestri, F., Soda, P., Sicilia, R., & Guarrasi, V. (2026) · Information Systems Frontiers · doi:10.1007/s10796-026-10741-3 · Cited by 2

Control Home Appliances Using Hand Gesture Recognition Based on Deep Learning and Arduino Uno via Infrared Signal

Le, V.-H., Nguyen, M.-Q., Te, T.-H., Phan, V.-N., & Do, H.-S. (2025) · Journal of Robotics and Control (JRC) · doi:10.18196/jrc.v6i6.27924 · Cited by 1

Multimodal medical image segmentation paradigm based on language-assisted transformer

Zhao, L., Wang, T., Tao, C., & Yang, E. (2026) · Neurocomputing · doi:10.1016/j.neucom.2026.133946 · Cited by 1

A survey on multimodal federated learning

Grosso, S., Benarba, N., Bouchenak, S., Esposito, R., & Polato, M. (2026) · Neural Computing and Applications · doi:10.1007/s00521-025-11815-0 · Cited by 1

A Hierarchical Framework of Central-Distributed LLM Negotiation and Specialized Model Orchestration for Multi-Robot Collaborative Assembly

Liu, Z., Xu, W., Yao, B., Qi, L., & Ba, M. (2026) · Procedia CIRP · doi:10.1016/j.procir.2026.05.337 · Cited by 1

Query Based Deep Contextual Video Understanding

Sarkar, S., Mandal, S., Chakraborty, J., & Nandi, S. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-26349-0_14 · Cited by 1

REBA-VLM: Enhanced risk mitigation in construction via Pose guided visual instruction tuning

Rahman, M. D., Kumara, L., Santhanam, S., & Bugalia, N. (2026) · International Symposium on Automation and Robotics in Construction (ISARC) · doi:10.22260/isarc2026/0117 · Cited by 1

Agentic multimodal framework for autonomous pavement crack detection and visual severity characterization

Abdallah, M., Ali, E., Kaloop, M. R., El-Diasty, M., & Hu, J. W. (2026) · Automation in Construction · doi:10.1016/j.autcon.2026.107116 · Cited by 1

Robust Onion: Peeling Open Vocab Object Detectors Under Noise

Pathak, P., Karuppasamy, M., Baranwal, A., Vyas, S., & Rawat, Y. S. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-37095-2_20 · Cited by 1

Zero-shot parcel instance delineation in fragmented agricultural landscapes: Cross-source evaluation and structure-aware validation

Calisto, J., Vecchio, M., Pincheira, M., & Antonelli, F. (2026) · Smart Agricultural Technology · doi:10.1016/j.atech.2026.102384 · Cited by 1

Embodied Intelligence Security with Vision-language Models: A Survey

Duan, J., Zhu, H., Liu, C., Li, S. Y., Tang, X., & Wang, Y. (2026) · Machine Intelligence Research · doi:10.1007/s11633-025-1626-x · Cited by 1

Exploring the capabilities of vision-language models to detect visual bugs in HTML5 canvas applications

Macklon, F., Boucher, C., & Bezemer, C. (2026) · Empirical Software Engineering · doi:10.1007/s10664-026-10906-3 · Cited by 1

PC2F: Language-guided Progressive Calibration and Cascade Filtering for Remote Sensing Visual Grounding

Sun, L., Wang, Z., Jiao, L., Liu, X., Li, L., Lu, X., Liu, F., Li, S., Zhang, D., Tian, X., et al. (2026) · Pattern Recognition · doi:10.1016/j.patcog.2026.114449 · Cited by 1

OCR-mediated modality dominance in vision–language models: implications for radiology AI trustworthiness

Akbasli, I. T., Oztürk, B., Serin, O., Doğan, V., Berikol, G. B., Comeau, D. S., Celi, L. A., & Ozguner, O. (2026) · Journal of medical imaging · doi:10.1117/1.jmi.13.4.045501 · Cited by 2

Multimodal Artificial Intelligence in Tissue Diagnostics

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