# LuxBorrow: From Pompier to Pompjee, Tracing Borrowing in Luxembourgish

arXiv: https://arxiv.org/abs/2603.10789 · HTML: https://mlsanity.com/paper/2603.10789/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 12 of its 46 references that are in the map.
- First posted on arXiv 11 Mar 2026.

## Builds on (most cited first, 12 of 12)

- [AlignScore: Evaluating Factual Consistency with a Unified Alignment Function](https://mlsanity.com/paper/2305.16739/) (2023)
- [GLUECoS : An Evaluation Benchmark for Code-Switched NLP](https://mlsanity.com/paper/2004.12376/) (2020)
- [LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluation](https://mlsanity.com/paper/2005.04322/) (2020)
- [An Open Dataset and Model for Language Identification](https://mlsanity.com/paper/2305.13820/) (2023)
- [Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text](https://mlsanity.com/paper/2106.10123/) (2021)
- [Subword-Level Language Identification for Intra-Word Code-Switching](https://mlsanity.com/paper/1904.01989/) (2019)
- [The futility of STILTs for the classification of lexical borrowings in Spanish](https://mlsanity.com/paper/2109.08607/) (2021)
- [Detecting Unassimilated Borrowings in Spanish: An Annotated Corpus and Approaches to Modeling](https://mlsanity.com/paper/2203.16169/) (2022)
- [Entropy and type-token ratio in gigaword corpora](https://mlsanity.com/paper/2411.10227/) (2024)
- [Neural Text Normalization for Luxembourgish using Real-Life Variation Data](https://mlsanity.com/paper/2412.09383/) (2024)
- [Borrowing or Codeswitching? Annotating for Finer-Grained Distinctions in Language Mixing](https://mlsanity.com/paper/2206.04973/) (2022)
- [Self-Consistent Decoding for More Factual Open Responses](https://mlsanity.com/paper/2403.00696/) (2024)

## Built on by (most cited first, 1 of 1)

- [Do LLMs Know What Luxembourgish Borrows? Probing Lexical Neology in Low-Resource Multilingual Models](https://mlsanity.com/paper/2605.21227/) (2026)

## Abstract (arXiv)

We present LuxBorrow, a borrowing-first analysis of Luxembourgish (LU) news spanning 27 years (1999-2025), covering 259,305 RTL articles and 43.7M tokens. Our pipeline combines sentence-level language identification (LU/DE/FR/EN) with a token-level borrowing resolver restricted to LU sentences, using lemmatization, a collected loanword registry, and compiled morphological and orthographic rules. Empirically, LU remains the matrix language across all documents, while multilingual practice is pervasive: 77.1% of articles include at least one donor language and 65.4% use three or four. Breadth does not imply intensity: median code-mixing index (CMI) increases from 3.90 (LU+1) to only 7.00 (LU+3), indicating localized insertions rather than balanced bilingual text. Domain and period summaries show moderate but persistent mixing, with CMI rising from 6.1 (1999-2007) to a peak of 8.4 in 2020. Token-level adaptations total 25,444 instances and exhibit a mixed profile: morphological 63.8%, orthographic 35.9%, lexical 0.3%. The most frequent individual rules are orthographic, such as on->oun and eur->er, while morphology is collectively dominant. Diachronically, code-switching intensifies, and morphologically adapted borrowings grow from a small base. French overwhelmingly supplies adapted items, with modest growth for German and negligible English. We advocate borrowing-centric evaluation, including borrowed token and type rates, donor entropy over borrowed items, and assimilation ratios, rather than relying only on document-level mixing indices.