Document Level Information Extraction

Document-level information extraction (DLE) aims to automatically transform unstructured documents into structured data, facilitating downstream applications. Current research emphasizes robust methods handling diverse document types and noisy data, employing large language models (LLMs) augmented with retrieval mechanisms or generative multi-modal networks to achieve state-of-the-art performance on tasks like key information extraction and line item recognition. This field is crucial for automating business processes and other applications requiring efficient document understanding, with ongoing efforts focused on improving accuracy, addressing challenges like event individuation and coreference resolution, and developing more comprehensive evaluation benchmarks.