Document Parsing

Document parsing focuses on automatically converting unstructured document images and PDFs into structured, machine-readable formats, enabling efficient information extraction and analysis. Current research emphasizes improving accuracy and robustness across diverse document types (e.g., scientific papers, receipts, forms) using multimodal models, advanced neural network architectures (like transformers and graph convolutional networks), and techniques such as contextual information integration and post-processing methods for robustness enhancement. This field is crucial for advancing various applications, including digital humanities research, automated document processing, and user interface interaction, by enabling efficient analysis of large volumes of textual and visual data.