In recent years, the problem of scene text extraction from images has received extensive
attention and significant progress. However, text extraction from scholarly figures such as …

We introduce a simple new approach to the problem of understanding documents where
non-trivial layout influences the local semantics. To this end, we modify the Transformer …

Automatic information extraction, eg, into a tabular format, is crucial for leveraging
knowledge in large text collections. Yet, creating such extraction pipelines for custom target …

With tremendous amounts of texts across the Internet nowadays, it is incredibly difficult for
people to manually seek for valuable knowledge from massive corpora, thus automatic …

In recent years, natural language processing has gained significant popularity in various
sectors, including the legal domain. This paper presents NeCo Team's solutions to the …

Document retrieval for domain-specific has been an important and challenging research in
NLP, particularly legal documents. The main challenge in the legal domain is the close …

In this paper, we examine an important recent rule-based information extraction (IE)
technique named Boosted Wrapper Induction (BWI), by conducting experiments on a wider …

In this paper, we present a system to showcase the capabilities of the latest state-of-the-art
retrieval augmented generation models trained on knowledge-intensive language tasks …

Background: In the information extraction and natural language processing domain,
accessible datasets are crucial to reproduce and compare results. Publicly available …

Abstract Information Extraction (IE) from document images is challenging due to the high
variability of layout formats. Deep models such as etc. In this work, we propose a novel …