LtzGLUE: Luxembourgish General Language Understanding Evaluation

MCML Authors

Felicia Körner

→ Group Barbara Plank
 AI and Computational Linguistics

Barbara Plank

Prof. Dr.

Core PI

AI and Computational Linguistics

Abstract

This paper presents ltzGLUE, the first Natural Language Understanding (NLU) benchmark for Luxembourgish (LTZ) based on the popular GLUE benchmark for English. Although NLU tasks are available for many european languages nowadays, LTZ is one of the official national languages that is often overlooked. We introduce new tasks and reuse existing ones to introduce the first official NLU benchmark and accompanying evaluation of encoder models for the language. Our tasks include common natural language processing tasks in binary and multi-class classification settings, including named entity recognition, topic classification, and intent classification. We evaluate various pre-trained language models for LTZ to present an overview of the current capabilities of these models on the LTZ language.

inproceedings PKL+26

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Findings @ACL 2026

Findings at the 64th Annual Meeting of the Association for Computational Linguistics. San Diego, CA, USA, Jul 02-07, 2026.

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Authors

A. Plum • F. Körner • A.-M. Lutgen • L. Bernardy • F. Philippy • E. Milano • N. Rehlinger • C. Lothritz • T. Ranasinghe • B. Plank • C. Purschke

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Links

DOI GitHub

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Research Area

 B2 | Natural Language Processing