This repository aggregates academic papers on data augmentation techniques for natural language processing. It organizes resources by NLP task categories including text classification, translation, summarization, question-answering, sequence tagging, parsing, dialogue, and more. The collection is based on a peer-reviewed survey published at ACL 2021 and serves as a reference for researchers and practitioners studying data augmentation in deep learning contexts.