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ltzGLUE: Luxembourgish General Language Understanding Evaluation

arXiv 2604.17976 ↗First posted 20 Apr 2026cs.CLcited by 0

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Abstract (arXiv)

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 construct 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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 27 of its 60 references that are in the map. First posted on arXiv 20 Apr 2026.

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27 of 60 references.

References · 27

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15 more
  1. 2022GPT-NeoX-20B: An Open-Source Autoregressive Language Modelcited by 713
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  14. 2024Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to Luxembourgishcited by 3
  15. 2026Do LLMs Judge Distantly Supervised Named Entity Labels Well? Constructing the JudgeWEL Datasetcited by 1

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