How ML Linting Meaningfully Improves Adaptive Document Processing at Scale

ML linting is a technique used to enhance the performance of adaptive document processing systems. This method automatically identifies and flags potential errors or inconsistencies in machine learning model outputs, similar to how code linting works for software. By applying these checks, developers can improve the quality and reliability of AI models designed to extract information from diverse documents. This process is crucial for maintaining high accuracy and efficiency when processing documents at a large scale.