1 code implementation • 30 Mar 2023 • Carlos-Emiliano González-Gallardo, Emanuela Boros, Nancy Girdhar, Ahmed Hamdi, Jose G. Moreno, Antoine Doucet
Large language models (LLMs) have been leveraged for several years now, obtaining state-of-the-art performance in recognizing entities from modern documents.
1 code implementation • 11 Feb 2023 • Štěpán Šimsa, Milan Šulc, Michal Uřičář, Yash Patel, Ahmed Hamdi, Matěj Kocián, Matyáš Skalický, Jiří Matas, Antoine Doucet, Mickaël Coustaty, Dimosthenis Karatzas
This paper introduces the DocILE benchmark with the largest dataset of business documents for the tasks of Key Information Localization and Extraction and Line Item Recognition.
no code implementations • 29 Jan 2023 • Štěpán Šimsa, Milan Šulc, Matyáš Skalický, Yash Patel, Ahmed Hamdi
The DocILE 2023 competition, hosted as a lab at the CLEF 2023 conference and as an ICDAR 2023 competition, will run the first major benchmark for the tasks of Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR) from business documents.
1 code implementation • 23 Sep 2021 • Maud Ehrmann, Ahmed Hamdi, Elvys Linhares Pontes, Matteo Romanello, Antoine Doucet
After decades of massive digitisation, an unprecedented amount of historical documents is available in digital format, along with their machine-readable texts.
1 code implementation • CONLL 2020 • Emanuela Boros, Ahmed Hamdi, Elvys Linhares Pontes, Luis Adri{\'a}n Cabrera-Diego, Jose G. Moreno, Nicolas Sidere, Antoine Doucet
This paper tackles the task of named entity recognition (NER) applied to digitized historical texts obtained from processing digital images of newspapers using optical character recognition (OCR) techniques.
no code implementations • JEPTALNRECITAL 2013 • Ahmed Hamdi, Rahma Boujelbane, Nizar Habash, Alexis Nasr