Open Dataset

Open datasets are collections of readily available data used to train and evaluate machine learning models, addressing the need for large, high-quality data sources to advance AI research. Current research focuses on creating open datasets for diverse applications, including natural language processing, computer vision (e.g., object detection, image segmentation), and biomedical research (e.g., cancer multi-omics), often incorporating techniques like contrastive learning and pre-trained foundation models to improve model performance and efficiency. The availability of these datasets significantly accelerates progress in various AI fields by providing standardized benchmarks and facilitating collaborative research, ultimately leading to improved model development and real-world applications.