👉 A supervision weapon is a type of machine learning model designed to improve the quality and consistency of data labeling, particularly in scenarios where manual annotation is costly or time-consuming. It operates by learning from the inherent structure and patterns within a dataset, generating high-quality labels that align with human expectations. By doing so, it can guide or correct the labeling process performed by human annotators, ensuring that the final labeled data is more accurate and reliable. This approach is especially useful in complex tasks like image recognition, natural language processing, and other areas where maintaining data integrity is crucial for training effective machine learning models.
