This paper presents a practical approach to fine-grained information extraction. Through
plenty of authors' experiences in practically applying information extraction to business …

Recent advances in deep learning and natural language processing (NLP) have opened
many new opportunities for automatic text understanding and text processing in the medical …

Abstract Information extraction from documents has become great use of novel natural
language processing areas. Most of the entity extraction methodologies are variant in a …

Large language models with instruction-following capabilities open the door to a wider
group of users. However, when it comes to information extraction-a classic task in natural …

Text representation plays a vital role in retrieval-based question answering, especially in the
legal domain where documents are usually long and complicated. The better the question …

The task of data-to-text generation aims to generate descriptive texts conditioned on a
number of database records, and recent neural models have shown significant progress on …

Information extraction from multilingual text for conversational AI generally implements
natural language understanding (NLU) using multiple language-specific models, which may …

The speed with which new online content becomes available has exacerbated the well
known problem of information overload and motivated the innovation of techniques that help …

Information extraction from document images has received a lot of attention recently, due to
the need for digitizing a large volume of unstructured documents such as invoices, receipts …

The goal of an information retrieval system is to retrieve documents that are most relevant to
a given user query from a huge collection of documents, which usually requires time …