Label Extraction

Label extraction focuses on automatically assigning labels to data, reducing the need for expensive and time-consuming manual annotation. Current research emphasizes efficient methods for handling sparse and streaming data, leveraging techniques like rule-based systems integrated with large language models, forward-forward learning, and adaptive regression models for dynamic data streams. These advancements are crucial for improving the efficiency and scalability of machine learning applications across various domains, including medical image analysis, federated learning, and real-time object tracking.