Annotation System

Annotation systems are crucial for training machine learning models, particularly in areas like natural language processing and computer vision, aiming to efficiently and accurately label data for model training and evaluation. Current research focuses on automating annotation processes using large language models and other deep learning techniques, improving annotation quality through active learning strategies and addressing challenges like label noise and bias in existing datasets. These advancements are vital for improving the performance and reliability of AI systems across diverse applications, from medical image analysis and social media monitoring to understanding human behavior and automating tasks in various domains.