A curated collection of research papers, surveys, and resources focused on parameter-efficient fine-tuning techniques for deep learning models. It covers methods like adapter tuning, prefix tuning, prompt tuning, and LoRA across both vision and language models. The repository organizes resources by tuning strategy and includes implementation references.