Long Short Range Adapter

Long Short-Range Adapters are lightweight modules designed to efficiently adapt pre-trained large language and vision models to new tasks without retraining the entire model. Research focuses on improving adapter architectures, such as incorporating sparse and correlated structures or specialized filters for visual data, to enhance performance and reduce computational costs across diverse applications including text-video retrieval, speech enhancement, and image generation. This approach offers a significant advantage by enabling efficient transfer learning and reducing the need for extensive computational resources, thereby broadening access to advanced AI models for various domains.