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SAMPLe: SAM-based Optimizer for Prompt Learning in VLMs
Hossein Rajoli, Fatemeh Lotfi, Niloufar Alipour Talemi +3
Pre-trained Vision-Language Models (VLMs) like CLIP have proven highly effective as foundation models for various downstream applications. However, prompt learning in VLMs encounte…
Hyper-ICL: Attention Calibration with Hyperbolic Anchor Distillation for Multimodal In-Context Learning
Niloufar Alipour Talemi, Hossein Kashiani, Fatemeh Afghah
Multimodal In-Context Learning (ICL) has emerged as a practical inference paradigm for Multimodal Large Language Models, where a small set of interleaved image-text In-Context Demo…
PromptMAD: Cross-Modal Prompting for Multi-Class Visual Anomaly Localization
Duncan McCain, Hossein Kashiani, Fatemeh Afghah
Visual anomaly detection in multi-class settings poses significant challenges due to the diversity of object categories, the scarcity of anomalous examples, and the presence of cam…
Agentic AI in Remote Sensing: Foundations, Taxonomy, and Emerging Systems
Niloufar Alipour Talemi, Julia Boone, Fatemeh Afghah
The paradigm of Earth Observation analysis is shifting from static deep learning models to autonomous agentic AI. Although recent vision foundation models and multimodal large lang…