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LLMs improve Luxembourgish borrowing detection with knowledge graph prompts

作者 PulseAugur 编辑部 · [2 个来源] ·

Researchers have developed a new benchmark, LexNeo-Bench, to evaluate how well large language models understand lexical borrowing in low-resource languages like Luxembourgish. The benchmark, derived from a Luxembourgish news corpus, labels tokens as native or borrowed from French, German, or English. When prompted with a linguistic knowledge graph, LLMs showed significantly improved accuracy in classifying borrowed words, narrowing the performance gap between smaller and larger models. AI

影响 Enhances LLM evaluation for low-resource languages, potentially improving writing assistance tools for diverse linguistic communities.

排序理由 The cluster describes an academic paper introducing a new benchmark and evaluation methodology for LLMs.

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

报道来源 [2]

  1. arXiv cs.CL TIER_1 English(EN) · Nina Hosseini-Kivanani ·

    Do LLMs Know What Luxembourgish Borrows? Probing Lexical Neology in Low-Resource Multilingual Models

    Large language models (LLMs) are increasingly used for writing assistance in small contact languages, yet it is unclear whether they respect community norms around lexical borrowing and neology. We introduce LexNeo-Bench, a 3{,}050-instance token-level benchmark derived from LuxB…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Do LLMs Know What Luxembourgish Borrows? Probing Lexical Neology in Low-Resource Multilingual Models

    Large language models (LLMs) are increasingly used for writing assistance in small contact languages, yet it is unclear whether they respect community norms around lexical borrowing and neology. We introduce LexNeo-Bench, a 3{,}050-instance token-level benchmark derived from LuxB…

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