Work

How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP

Year: 2026

Type: conference-paper

Abstract: Kushal Tatariya, Artur Kulmizev, Wessel Poelman, Esther Ploeger, Marcel Bollmann, Johannes Bjerva, Jiaming Luo, Heather Lent, Miryam de Lhoneux. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

Source: Proceedings of the conference - Association for Computational Linguistics. Meeting

DOI: 10.18653/v1/2026.acl-long.1373

Authors: Kushal Tatariya, Artur Kulmizev, Wessel Poelman, Esther Ploeger, Marcel Bollmann, Johannes Bjerva, Jiaming Luo, Heather Lent, Miryam de Lhoneux

Institutions: KU Leuven, UCLouvain, Aalborg University, Linköping University, Google (United States)

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: Vlaams Supercomputer Centrum, European Commission, Fonds Wetenschappelijk Onderzoek, KU Leuven, Vetenskapsrådet, Onderzoeksraad, KU Leuven, Vlaamse regering, HORIZON EUROPE Framework Programme

Awards: Democratize Trustworthy and Efficient Large Language Model Technology for Europe, Fairness in Multilingual NLP

OpenAlex ID: W4404389739

FWCI:

Cites:

Cited by:

Related to: 10