Can Vision-Language Models Understand Construction Workers? An Exploratory Study
Fuente:
arXiv
Saved in:
| Main Authors: | Bui, Hieu, Chodosh, Nathaniel E., Tavakoli, Arash |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Can Vision Language Models Understand Mimed Actions?
by: Cho, Hyundong, et al.
Published: (2025)
by: Cho, Hyundong, et al.
Published: (2025)
Lost in Space: Probing Fine-grained Spatial Understanding in Vision and Language Resamplers
by: Pantazopoulos, Georgios, et al.
Published: (2024)
by: Pantazopoulos, Georgios, et al.
Published: (2024)
VTCBench: Can Vision-Language Models Understand Long Context with Vision-Text Compression?
by: Zhao, Hongbo, et al.
Published: (2025)
by: Zhao, Hongbo, et al.
Published: (2025)
TCP-SSM: Efficient Vision State Space Models with Token-Conditioned Poles
by: Shoouri, Sara, et al.
Published: (2026)
by: Shoouri, Sara, et al.
Published: (2026)
Understanding Counting Mechanisms in Large Language and Vision-Language Models
by: Hasani, Hosein, et al.
Published: (2025)
by: Hasani, Hosein, et al.
Published: (2025)
Can Multimodal Large Language Models Understand Pathologic Movements? A Pilot Study on Seizure Semiology
by: Zhang, Lina, et al.
Published: (2026)
by: Zhang, Lina, et al.
Published: (2026)
Environmental Understanding Vision-Language Model for Embodied Agent
by: Bang, Jinsik, et al.
Published: (2026)
by: Bang, Jinsik, et al.
Published: (2026)
Review of Hallucination Understanding in Large Language and Vision Models
by: Ho, Zhengyi, et al.
Published: (2025)
by: Ho, Zhengyi, et al.
Published: (2025)
Can Vision-Language Models Replace Human Annotators: A Case Study with CelebA Dataset
by: Lu, Haoming, et al.
Published: (2024)
by: Lu, Haoming, et al.
Published: (2024)
Can Multimodal Large Language Models Truly Understand Small Objects?
by: Han, Fujun, et al.
Published: (2026)
by: Han, Fujun, et al.
Published: (2026)
Large Language Models Can Understanding Depth from Monocular Images
by: Xia, Zhongyi, et al.
Published: (2024)
by: Xia, Zhongyi, et al.
Published: (2024)
Adapting Vision-Language Models for E-commerce Understanding at Scale
by: Nulli, Matteo, et al.
Published: (2026)
by: Nulli, Matteo, et al.
Published: (2026)
In-Context Learning Improves Compositional Understanding of Vision-Language Models
by: Nulli, Matteo, et al.
Published: (2024)
by: Nulli, Matteo, et al.
Published: (2024)
RAU: Reference-based Anatomical Understanding with Vision Language Models
by: Li, Yiwei, et al.
Published: (2025)
by: Li, Yiwei, et al.
Published: (2025)
Reasoning under Vision: Understanding Visual-Spatial Cognition in Vision-Language Models for CAPTCHA
by: Song, Python, et al.
Published: (2025)
by: Song, Python, et al.
Published: (2025)
Brain Tumor Segmentation in MRI Images with 3D U-Net and Contextual Transformer
by: Nguyen, Thien-Qua T., et al.
Published: (2024)
by: Nguyen, Thien-Qua T., et al.
Published: (2024)
Diagnosing Bottlenecks in Data Visualization Understanding by Vision-Language Models
by: Tartaglini, Alexa R., et al.
Published: (2025)
by: Tartaglini, Alexa R., et al.
Published: (2025)
AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?
by: Bao, Han, et al.
Published: (2024)
by: Bao, Han, et al.
Published: (2024)
Benchmarking Vision Language Models for Cultural Understanding
by: Nayak, Shravan, et al.
Published: (2024)
by: Nayak, Shravan, et al.
Published: (2024)
YoChameleon: Personalized Vision and Language Generation
by: Nguyen, Thao, et al.
Published: (2025)
by: Nguyen, Thao, et al.
Published: (2025)
RE-VLM: Event-Augmented Vision-Language Model for Scene Understanding
by: Liu, Hanqing, et al.
Published: (2026)
by: Liu, Hanqing, et al.
Published: (2026)
Are Unified Vision-Language Models Necessary: Generalization Across Understanding and Generation
by: Zhang, Jihai, et al.
Published: (2025)
by: Zhang, Jihai, et al.
Published: (2025)
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
by: Baechler, Gilles, et al.
Published: (2024)
by: Baechler, Gilles, et al.
Published: (2024)
FlowLearn: Evaluating Large Vision-Language Models on Flowchart Understanding
by: Pan, Huitong, et al.
Published: (2024)
by: Pan, Huitong, et al.
Published: (2024)
NegVQA: Can Vision Language Models Understand Negation?
by: Zhang, Yuhui, et al.
Published: (2025)
by: Zhang, Yuhui, et al.
Published: (2025)
GameVerse: Can Vision-Language Models Learn from Video-based Reflection?
by: Zhang, Kuan, et al.
Published: (2026)
by: Zhang, Kuan, et al.
Published: (2026)
SD-VLM: Spatial Measuring and Understanding with Depth-Encoded Vision-Language Models
by: Chen, Pingyi, et al.
Published: (2025)
by: Chen, Pingyi, et al.
Published: (2025)
SARVLM: A Vision Language Foundation Model for Semantic Understanding in SAR Imagery
by: Ma, Qiwei, et al.
Published: (2025)
by: Ma, Qiwei, et al.
Published: (2025)
Hierarchical Question-Answering for Driving Scene Understanding Using Vision-Language Models
by: Mohamud, Safaa Abdullahi Moallim, et al.
Published: (2025)
by: Mohamud, Safaa Abdullahi Moallim, et al.
Published: (2025)
GazeVLM: A Vision-Language Model for Multi-Task Gaze Understanding
by: Mathew, Athul M., et al.
Published: (2025)
by: Mathew, Athul M., et al.
Published: (2025)
Can Vision-Language Models Solve Visual Math Equations?
by: Choudhury, Monjoy Narayan, et al.
Published: (2025)
by: Choudhury, Monjoy Narayan, et al.
Published: (2025)
Can Vision-Language Models be a Good Guesser? Exploring VLMs for Times and Location Reasoning
by: Zhang, Gengyuan, et al.
Published: (2023)
by: Zhang, Gengyuan, et al.
Published: (2023)
Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
by: Clark, Christopher, et al.
Published: (2026)
by: Clark, Christopher, et al.
Published: (2026)
Understanding Pruning Regimes in Vision-Language Models Through Domain-Aware Layer Selection
by: Khaki, Saeed, et al.
Published: (2026)
by: Khaki, Saeed, et al.
Published: (2026)
OmniPT: Unleashing the Potential of Large Vision Language Models for Pedestrian Tracking and Understanding
by: Fu, Teng, et al.
Published: (2025)
by: Fu, Teng, et al.
Published: (2025)
Rice-VL: Evaluating Vision-Language Models for Cultural Understanding Across ASEAN Countries
by: Pranav, Tushar, et al.
Published: (2025)
by: Pranav, Tushar, et al.
Published: (2025)
InsightSee: Advancing Multi-agent Vision-Language Models for Enhanced Visual Understanding
by: Zhang, Huaxiang, et al.
Published: (2024)
by: Zhang, Huaxiang, et al.
Published: (2024)
Can Vision Language Models Judge Action Quality? An Empirical Evaluation
by: Freitas, Miguel Monte e, et al.
Published: (2026)
by: Freitas, Miguel Monte e, et al.
Published: (2026)
A Unified Understanding of Adversarial Vulnerability Regarding Unimodal Models and Vision-Language Pre-training Models
by: Zheng, Haonan, et al.
Published: (2024)
by: Zheng, Haonan, et al.
Published: (2024)
Your Vision-Language Model Can't Even Count to 20: Exposing the Failures of VLMs in Compositional Counting
by: Guo, Xuyang, et al.
Published: (2025)
by: Guo, Xuyang, et al.
Published: (2025)
Similar Items
-
Can Vision Language Models Understand Mimed Actions?
by: Cho, Hyundong, et al.
Published: (2025) -
Lost in Space: Probing Fine-grained Spatial Understanding in Vision and Language Resamplers
by: Pantazopoulos, Georgios, et al.
Published: (2024) -
VTCBench: Can Vision-Language Models Understand Long Context with Vision-Text Compression?
by: Zhao, Hongbo, et al.
Published: (2025) -
TCP-SSM: Efficient Vision State Space Models with Token-Conditioned Poles
by: Shoouri, Sara, et al.
Published: (2026) -
Understanding Counting Mechanisms in Large Language and Vision-Language Models
by: Hasani, Hosein, et al.
Published: (2025)