Work

Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization

Year: 2026

Type: conference-paper

Abstract: Negar Foroutan, Clara Meister, Debjit Paul, Joel Niklaus, Sina Ahmadi, Antoine Bosselut, Rico Sennrich. 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.342

Authors: Negar Foroutan, Clara Meister, Debjit Paul, Joel Niklaus, Sina Ahmadi, Antoine Bosselut, Rico Sennrich

Institutions: École Polytechnique Fédérale de Lausanne, University of Zurich

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Reduced inequalities

Open Access status: hybrid

Funders: National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Innosuisse - Schweizerische Agentur für Innovationsförderung

Awards: Interfacing Neural and Symbolic Knowledge in Natural Language Systems, Multitask Learning with Multilingual Resources for Better Natural Language Understanding, G8503654337

OpenAlex ID: W7166801475

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