Research Progress and Future Prospects of Data Distillation Technology Supporting Data

This dataset consists of two core components: a literature bibliography list and a classification table of data distillation methods and their applications. It is constructed based on 88 representative Chinese and English literatures retrieved and selected from databases such as CNKI and Web of Science during 2021-2025. The literature bibliography list systematically collects key information including authors, titles, literature sources, and publication years of relevant research in the field of data distillation. The classification table sorts out the characteristics of each method and corresponding literature support from the dimensions of algorithm types (meta-learning, data matching) and application fields (computer vision, smart healthcare, recommender systems, natural language processing, graph learning). The dataset comprehensively covers the core algorithms, multi-domain practices, and cutting-edge directions of data distillation technology, providing systematic and standardized supporting data for sorting out research progress, conducting algorithm comparison and analysis, and expanding applications in this field. It is in line with the requirements of Data Analysis and Knowledge Discovery for the accessibility and verifiability of paper supporting data.