Document Understanding Task

Document understanding tasks aim to enable computers to comprehend the content and structure of documents, including text, images, and layout information, to perform tasks like key information extraction and visual question answering. Current research heavily utilizes large language models (LLMs) and multimodal LLMs, often incorporating graph attention networks or U-Net architectures, to process this information effectively, with a focus on improving data efficiency and generalization across diverse document types and languages. These advancements are crucial for various applications, including automating document processing in fields like finance, law, and historical archives, and improving accessibility for visually impaired individuals.