4 papers
LuxIT: A Luxembourgish Instruction Tuning Dataset from Monolingual Seed Data
Julian Valline, Cedric Lothritz, Siwen Guo +1
The effectiveness of instruction-tuned Large Language Models (LLMs) is often limited in low-resource linguistic settings due to a lack of high-quality training data. We introduce L…
ltzGLUE: Luxembourgish General Language Understanding Evaluation
Alistair Plum, Felicia Körner, Anne-Marie Lutgen +8
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 ar…
Testing Low-Resource Language Support in LLMs Using Language Proficiency Exams: the Case of Luxembourgish
Cedric Lothritz, Jordi Cabot, Laura Bernardy
Large Language Models (LLMs) have become an increasingly important tool in research and society at large. While LLMs are regularly used all over the world by experts and lay-people…
Mind the Language Gap: Automated and Augmented Evaluation of Bias in LLMs for High- and Low-Resource Languages
Alessio Buscemi, Cédric Lothritz, Sergio Morales +4
Large Language Models (LLMs) have exhibited impressive natural language processing capabilities but often perpetuate social biases inherent in their training data. To address this,…