Annotation Pipeline

Annotation pipelines are automated processes for labeling data, crucial for training machine learning models, particularly in complex domains like object detection and scientific information extraction. Current research focuses on improving annotation accuracy and efficiency through techniques like leveraging large language models (LLMs) and semi-supervised methods, addressing challenges such as data bias and the need for diverse, high-quality datasets. These advancements are vital for accelerating scientific discovery and improving the performance of AI systems across various applications, from autonomous vehicles to medical diagnosis.