CATCH: A Modular Cross-domain Adaptive Template with Hook

The recent introduction of CATCH, a modular cross-domain adaptive template, aims to enhance Visual Question Answering (VQA) systems by addressing their limitations in out-of-domain scenarios. While models like LLaVA have shown great success in natural image domains, they struggle with generalization in fields such as remote sensing and medical imaging. CATCH seeks to improve domain adaptation, making VQA more versatile and effective across various applications, which is crucial for advancing AI's capabilities in diverse real-world situations.