Domain Datasets

Domain datasets are collections of data specific to a particular area of application, crucial for training and evaluating machine learning models. Current research focuses on improving model performance on out-of-domain data, employing techniques like data augmentation with synthetic data, parameter-efficient fine-tuning, and data selection strategies guided by smaller models. These advancements aim to enhance the robustness and generalizability of AI systems across diverse applications, addressing challenges like limited labeled data and domain shifts, ultimately leading to more reliable and effective AI models.