Retrieval-based augmentations that aim to incorporate knowledge from an external
database into language models have achieved great success in various knowledge …

Large Language Models (LLM) have revolutionized Natural Language Processing (NLP),
improving state-of-the-art on many existing tasks and exhibiting emergent capabilities …

Typically, information extraction (IE) requires a pipeline approach: first, a sequence labeling
model is trained on manually annotated documents to extract relevant spans; then, when a …

Large language models have unlocked strong multi-task capabilities from reading instructive
prompts. However, recent studies have shown that existing large models still have difficulty …

Most administrative documents take a semi-structured form (invoices, payslips, etc.).
Extracting information from this type of document is still challenging because of the …

Abstract Information extraction from documents such as receipts or invoices is a fundamental
and crucial step for office automation. Many approaches focus on extracting entities and …

Abstract Domain specific information retrieval process has been a prominent and ongoing
research in the field of natural language processing. Many researchers have incorporated …

This paper focuses on how to take advantage of external knowledge bases (KBs) to improve
recurrent neural networks for machine reading. Traditional methods that exploit knowledge …

Extracting structured data from visually rich documents like invoices, receipts, financial
statements, and tax forms is key to automating many business workflows. However, building …

Abstract Knowledge management is crucial for construction safety management. Widely
collected and well-organized safety-related documents are recognized to be significant in …