Document Visual Question Answering with CIVQA: Czech Invoice Visual Question Answering Dataset

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F23%3A00132396" target="_blank" >RIV/00216224:14330/23:00132396 - isvavai.cz</a>

Result on the web

<a href="https://www.fi.muni.cz/usr/sojka/papers/scavnicka-stefanik-sojka-raslan-2023.pdf" target="_blank" >https://www.fi.muni.cz/usr/sojka/papers/scavnicka-stefanik-sojka-raslan-2023.pdf</a>

DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Document Visual Question Answering with CIVQA: Czech Invoice Visual Question Answering Dataset

Original language description

Applications of document processing become increasingly popular across multiple industries, resulting in a growing amount of research on the applications of artificial intelligence in document processing (Document AI). This paper focuses on a subtask of Document AI, Document Visual Question Answering (DVQA), recently getting well-deserved attention thanks to its universality. However, the limited availability of data sources for languages outside English restrains the applicability of DVQA in non-English languages. <p> For this reason, we created the CIVQA (Czech Inovice Visual Question Answering) dataset covering 15 entities of financial documents, consisting of more than 6,000 invoices in the Czech language. </p> <p> We used the CIVQA dataset to create the first-of-its-kind DVQA models specifically tailored for applications to Czech documents. Striving to create DVQA models able to generalize, we specifically evaluate our models on the entities not covered in the training mix and find that multilingual LayoutLM models are able to respond to questions about previously unseen entities substantially more accurately than other models. </p> <p> The CIVQA dataset and experiment observations offer new opportunities for Document AI in the Czech Republic, with potential applications in research and commercial fields.</p>

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

<a href="/en/project/EG21_374%2F0026711" target="_blank" >EG21_374/0026711: Smart back office</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Recent Advances in Slavonic Natural Language Processing (RASLAN 2023)

ISBN

9788026317937

ISSN

2336-4289

e-ISSN

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Number of pages

12

Pages from-to

23-34

Publisher name

Tribun EU

Place of publication

Brno

Event location

Kouty nad Desnou

Event date

Dec 8, 2023

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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