首个卢森堡语自然语言理解基准，填补小语种研究空白
ltzGLUE: Luxembourgish General Language Understanding Evaluation
- 基于GLUE构建卢森堡语专用评测集
- 涵盖命名实体识别等多类分类任务
- 为小语种模型评估提供首个官方标准
本文提出首个基于英语GLUE基准的卢森堡语（LTZ）自然语言理解（NLU）评测集ltzGLUE。尽管当前已有多种欧洲语言的NLU任务，卢森堡语作为官方语言仍常被忽视。我们构建新任务并复用现有任务，建立首个官方的卢森堡语NLU基准及其配套评估体系。任务包括二分类与多分类场景下的常见NLP任务，如命名实体识别、主题分类和意图分类。我们对多种预训练语言模型在卢森堡语上的表现进行评估，呈现当前模型在该语言上的能力概况。
原文摘要 · Abstract (English)
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.
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