This repository aggregates academic papers on parameter-efficient transfer learning techniques, including prompt tuning, adapter methods, and unified approaches. It targets researchers and practitioners working with large-scale vision-language models who want to adapt these models efficiently for downstream tasks without full fine-tuning.