Synthetic Label

Synthetic labels are artificially generated data labels used to train machine learning models, particularly when real-world labeled data is scarce, expensive, or noisy. Current research focuses on generating high-quality synthetic labels using techniques like diffusion models and large language models (LLMs), often incorporating contextual information to improve realism and relevance. This approach is proving valuable across diverse fields, from medical image analysis and histopathology to image retrieval and scene text detection, by enabling efficient model training and improving performance, especially in zero-shot or low-data scenarios. The ability to create effective synthetic labels is significantly advancing the development and application of machine learning models in various domains.