b'@online{Poggi_2507.15576,'b'\nTITLE = {Smart Eyes for Silent Threats: {VLMs} and In-Context Learning for {THz} Imaging},\nAUTHOR = {Poggi, Nicolas and Agnihotri, Shashank and Keuper, Margret},\nLANGUAGE = {eng},\nURL = {https://arxiv.org/abs/2507.15576},\nEPRINT = {2507.15576},\nEPRINTTYPE = {arXiv},\nYEAR = {2025},\nMARGINALMARK = {$\\bullet$},\nABSTRACT = {Terahertz (THz) imaging enables non-invasive analysis for applications such as security screening and material classification, but effective image classification remains challenging due to limited annotations, low resolution, and visual ambiguity. We introduce In-Context Learning (ICL) with Vision-Language Models (VLMs) as a flexible, interpretable alternative that requires no fine-tuning. Using a modality-aligned prompting framework, we adapt two open-weight VLMs to the THz domain and evaluate them under zero-shot and one-shot settings. Our results show that ICL improves classification and interpretability in low-data regimes. This is the first application of ICL-enhanced VLMs to THz imaging, offering a promising direction for resource-constrained scientific domains. Code: \\href{https://github.com/Nicolas-Poggi/Project_THz_Classification/tree/main}{GitHub repository}.},\n}\n'