---
title: "ltzGLUE — paper by Plum et al. (2026) — summary and ideas"
description: "The authors also release two new encoders, LTZ-E1 mini and base. 55 references. Among them: 0."
authors: ["Alistair Plum", "Felicia Körner", "Anne-Marie Lutgen", "Laura Bernardy", "Fred Philippy", "Emilia Milano", "Nils Rehlinger", "Cedric Lothritz", "Tharindu Ranasinghe", "Barbara Plank", "Christoph Purschke"]
year: 2026
venue: "Findings of the Association for Computational Linguistics: ACL 2026"
source: "https://aclanthology.org/2026.findings-acl.476/"
doi: "10.18653/v1/2026.findings-acl.476"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/plum-2026-ltzglue-luxembourgish-general-language-understanding/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/plum-2026-ltzglue-luxembourgish-general-language-understanding/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/40/) / ltzGLUE: Luxembourgish General Language Understanding Evaluation

# ltzGLUE: Luxembourgish General Language Understanding Evaluation

**Authors:** [Alistair Plum](https://md.research.elamur.ai/free/en/authors/alistair-plum/), [Felicia Körner](https://md.research.elamur.ai/free/en/authors/felicia-korner/), [Anne-Marie Lutgen](https://md.research.elamur.ai/free/en/authors/anne-marie-lutgen/), [Laura Bernardy](https://md.research.elamur.ai/free/en/authors/laura-bernardy/), [Fred Philippy](https://md.research.elamur.ai/free/en/authors/fred-philippy/), Emilia Milano, [Nils Rehlinger](https://md.research.elamur.ai/free/en/authors/nils-rehlinger/), [Cedric Lothritz](https://md.research.elamur.ai/free/en/authors/cedric-lothritz/), [Tharindu Ranasinghe](https://md.research.elamur.ai/free/en/authors/tharindu-ranasinghe/), [Barbara Plank](https://md.research.elamur.ai/free/en/authors/barbara-plank/) and [Christoph Purschke](https://md.research.elamur.ai/free/en/authors/christoph-purschke/) · **Year:** 2026 · **Venue:** [Findings of the Association for Computational Linguistics: ACL 2026](https://md.research.elamur.ai/free/en/venues/findings/) ([Findings of the Association for Computational Linguistics 2026](https://md.research.elamur.ai/free/en/venues/findings/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.findings-acl.476/) · [PDF](https://aclanthology.org/2026.findings-acl.476.pdf) · [DOI 10.18653/v1/2026.findings-acl.476](https://doi.org/10.18653/v1/2026.findings-acl.476) · [OpenAlex](https://openalex.org/W7166852551)

**Citations:** 0 citations (OpenAlex, 2026-10-14)

## Summary
Luxembourgish (LTZ) has roughly 400k speakers and few NLU resources. Most existing tasks come from news text and often contain under a thousand instances, so model comparisons for the language are unreliable. The authors address this with ltzGLUE, a GLUE-style benchmark of eight sentence- and token-level classification tasks. Some tasks are reused from earlier work and others are newly built.

The new data comes mainly from RTL news articles and LTZ Wikipedia:
- **Headline acceptability:** headlines are swapped between articles using TF–IDF similarity, with filters against trivial matches.
- **Sentiment:** sentences are manually annotated.
- **Linguistic acceptability:** sentences from the Luxembourgish Online Dictionary are deliberately corrupted.

The authors also release two new encoders, LTZ-E1 mini and base. They compare these with existing encoders and with prompted LLMs. Fine-tuned encoders generally win, especially on structured or fine-grained linguistic tasks. Prompted LLMs are competitive only on coarse semantic tasks such as topic classification, and their outputs vary across runs and prompts. The benchmark gives the community a shared reference point for evaluating LTZ language understanding.

## Key points
- ltzGLUE has 8 tasks, including NER, topic classification, intent classification, textual entailment, sentiment analysis, headline acceptability, and linguistic acceptability (binary and multi-class). Data is released under CC BY at github.com/plumaj/ltzGLUE.
- Headline acceptability uses 30k RTL articles from the 20 most frequent categories, split into 20k train, 3k dev, and 6k test. Donor headlines for negative examples must be at least 30 days apart from the source article.
- For sentiment, 4,583 sentences from RTL commentary and reader-letter sections were labelled by two native speakers. Cohen's Kappa was 0.45, and disagreements were resolved jointly.
- Linguistic acceptability uses LOD sentences with four error types: subject-verb agreement, adjective inflection, deleted words, and spelling variants from Spellchecker.lu. The split is 70/10/20.
- New models LTZ-E1 (mini/base) are published at huggingface.co/instilux. LTZ-specific encoders such as LuxemBERT do well on lexical tasks but are less stable on complex inference.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

## Institutions

- [Ludwig-Maximilians-Universität München](https://md.research.elamur.ai/free/en/universities/ludwig-maximilians-universitat-munchen/) — University, Munich, Germany · 113 works · 56,817 citations
- [Lancaster University](https://md.research.elamur.ai/free/en/universities/lancaster-university/) — University, Lancaster, United Kingdom · 36 works · 1,615 citations
- [Munich Center for Machine Learning](https://md.research.elamur.ai/free/en/universities/munich-center-for-machine-learning/) — University, Munich, Germany · 62 works · 1,167 citations
- [University of Luxembourg](https://md.research.elamur.ai/free/en/universities/university-of-luxembourg/) — University, Luxembourg, Luxembourg · 28 works · 337 citations
- [Luxembourg Institute of Science and Technology](https://md.research.elamur.ai/free/en/labs/luxembourg-institute-of-science-and-technology/) — Research institute, Belvaux, Luxembourg · 6 works · 9 citations

📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 18,614 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 17,965 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 17,450 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 17,296 works

## Cite

Cite as: Alistair Plum, Felicia Körner, Anne-Marie Lutgen, Laura Bernardy, Fred Philippy, Emilia Milano, Nils Rehlinger, Cedric Lothritz, Tharindu Ranasinghe, Barbara Plank and Christoph Purschke. 2026. ltzGLUE: Luxembourgish General Language Understanding Evaluation. Findings of the Association for Computational Linguistics: ACL 2026.

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{plum2026ltzglue,
  title = {{ltzGLUE: Luxembourgish General Language Understanding Evaluation}},
  author = {Alistair Plum, Felicia Körner, Anne-Marie Lutgen, Laura Bernardy, Fred Philippy, Emilia Milano, Nils Rehlinger, Cedric Lothritz, Tharindu Ranasinghe, Barbara Plank and Christoph Purschke},
  booktitle = {Findings of the Association for Computational Linguistics: ACL 2026},
  year = {2026},
  doi = {10.18653/v1/2026.findings-acl.476},
  url = {https://doi.org/10.18653/v1/2026.findings-acl.476}
}
```

- [← previous LST at MWE-2026 AdMIRe 2: Advancing Multimodal Idiomaticity Representation](https://md.research.elamur.ai/free/en/papers/qiu-2026-lst-mwe-2026-admire-2/)
- [next → LUMINA: Long-horizon Understanding for Multi-turn Interactive Agents](https://md.research.elamur.ai/free/en/papers/rakhsha-2026-lumina-long-horizon-understanding-multi/)
- [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/40/)

## References

55 references, 26 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Martine Adda-Decker, Thomas Pellegrini, Eric Bilinski, and Gilles Adda. 2008. Developments of “Lëtzebuergesch” Resources for Automatic Speech Processing and Linguistic Studies. In Proceedings of LREC. [find](https://scholar.google.com/scholar?q=Martine+Adda%2DDecker%2C+Thomas+Pellegrini%2C+Eric+Bilinski%2C+and+Gilles+Adda%2E+2008%2E+Developments+of+%E2%80%9CL%C3%ABtzebuergesch%E2%80%9D+Resources+for+Automatic+Speech+Processing+and+Linguistic+Studies%2E+In+Proceedings+of+LREC%2E)
2. Valerio Basile, Livio Bioglio, Alessio Bosca, Cristina Bosco, and Viviana Patti. 2023. UINAUIL: A Unified Benchmark for Italian Natural Language Understanding. In Proceedings of ACL. [find](https://scholar.google.com/scholar?q=Valerio+Basile%2C+Livio+Bioglio%2C+Alessio+Bosca%2C+Cristina+Bosco%2C+and+Viviana+Patti%2E+2023%2E+UINAUIL%3A+A+Unified+Benchmark+for+Italian+Natural+Language+Understanding%2E+In+Proceedings+of+ACL%2E)
3. Laura Bernardy. 2022. A Luxembourgish GPT-2 Approach Based on Transfer Learning. Master’s thesis, University of Trier. [find](https://scholar.google.com/scholar?q=Laura+Bernardy%2E+2022%2E+A+Luxembourgish+GPT%2D2+Approach+Based+on+Transfer+Learning%2E+Master%E2%80%99s+thesis%2C+University+of+Trier%2E)
4. Sidney Black, Stella Biderman, Eric Hallahan, Quentin Anthony, Leo Gao, Laurence Golding, Horace He, Connor Leahy, Kyle McDonell, Jason Phang, Michael Pieler, Usvsn Sai Prashanth, Shivanshu Purohit, Laria Reynolds, Jonathan Tow, Ben Wang, and Samuel Weinbach. 2022. [GPT-NeoX-20B: An Open-Source Autoregressive Language Model](https://md.research.elamur.ai/free/en/papers/black-2022-gpt-neox-20b-open-source/). In Proceedings of BigScience.
5. Laurie Burchell, Alexandra Birch, Nikolay Bogoychev, and Kenneth Heafield. 2023. [An Open Dataset and Model for Language Identification](https://md.research.elamur.ai/free/en/papers/burchell-2023-open-dataset-model-language-identification/). In Proceedings of ACL.
6. Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020. [Unsupervised cross-lingual representation learning at scale](https://md.research.elamur.ai/free/en/papers/conneau-2020-unsupervised-cross-lingual-representation-learning/). In Proceedings of ACL.
7. Yin Cui, Menglin Jia, Tsung-Yi Lin, Yang Song, and Serge Belongie. 2019. Class-balanced loss based on effective number of samples. In Proceedings of CVPR. [find](https://scholar.google.com/scholar?q=Yin+Cui%2C+Menglin+Jia%2C+Tsung%2DYi+Lin%2C+Yang+Song%2C+and+Serge+Belongie%2E+2019%2E+Class%2Dbalanced+loss+based+on+effective+number+of+samples%2E+In+Proceedings+of+CVPR%2E)
8. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://md.research.elamur.ai/free/en/papers/devlin-2019-bert-pre-training-deep-bidirectional/). In Proceedings of NAACL-HLT.
9. William B. Dolan and Chris Brockett. 2005. [Automatically constructing a corpus of sentential paraphrases](https://md.research.elamur.ai/free/en/papers/dolan-2005-automatically-constructing-corpus-sentential-paraphrases/). In Proceedings of IWP.
10. Daniela Gierschek. 2022. Detection of Sentiment in Luxembourgish User Comments. Ph.D. thesis, University of Luxembourg. [find](https://scholar.google.com/scholar?q=Daniela+Gierschek%2E+2022%2E+Detection+of+Sentiment+in+Luxembourgish+User+Comments%2E+Ph%2ED%2E+thesis%2C+University+of+Luxembourg%2E)
11. Peter Gilles. 2019. 39. Komplexe Überdachung II: Luxemburg. Die Genese Einer Neuen Nationalsprache, pages 1039–1060. De Gruyter Mouton. [find](https://scholar.google.com/scholar?q=Peter+Gilles%2E+2019%2E+39%2E+Komplexe+%C3%9Cberdachung+II%3A+Luxemburg%2E+Die+Genese+Einer+Neuen+Nationalsprache%2C+pages+1039%E2%80%931060%2E+De+Gruyter+Mouton%2E)
12. R Bar Haim, Ido Dagan, Bill Dolan, Lisa Ferro, Danilo Giampiccolo, Bernardo Magnini, and Idan Szpektor. 2006. The second pascal recognising textual entailment challenge. In Proceedings of the Second PAS-CAL Challenges Workshop on Recognising Textual Entailment. [find](https://scholar.google.com/scholar?q=R+Bar+Haim%2C+Ido+Dagan%2C+Bill+Dolan%2C+Lisa+Ferro%2C+Danilo+Giampiccolo%2C+Bernardo+Magnini%2C+and+Idan+Szpektor%2E+2006%2E+The+second+pascal+recognising+textual+entailment+challenge%2E+In+Proceedings+of+the+Second+P)
13. Momchil Hardalov, Todor Mihaylov, Kiril Simov, and Preslav Nakov. 2023. BgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark. In Proceedings of RANLP. [find](https://scholar.google.com/scholar?q=Momchil+Hardalov%2C+Todor+Mihaylov%2C+Kiril+Simov%2C+and+Preslav+Nakov%2E+2023%2E+BgGLUE%3A+A+Bulgarian+General+Language+Understanding+Evaluation+Benchmark%2E+In+Proceedings+of+RANLP%2E)
14. Hansi Hettiarachchi, Tharindu Ranasinghe, Alistair Plum, Paul Rayson, Ruslan Mitkov, Mohamed Medhat Gaber, Damith Premasiri, Fiona Anting Tan, and Lasitha Uyangodage. 2026. Overview of the second workshop on language models for low-resource languages (LoResLM 2026). In Proceedings of the LoResLM. [find](https://scholar.google.com/scholar?q=Hansi+Hettiarachchi%2C+Tharindu+Ranasinghe%2C+Alistair+Plum%2C+Paul+Rayson%2C+Ruslan+Mitkov%2C+Mohamed+Medhat+Gaber%2C+Damith+Premasiri%2C+Fiona+Anting+Tan%2C+and+Lasitha+Uyangodage%2E+2026%2E+Overview+of+the+second+work)
15. J. Edward Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, Melvin Johnson, et al. 2020. [XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization](https://md.research.elamur.ai/free/en/papers/hu-2020-xtreme-massively-multilingual-multi-task/). In Proceedings of ICML.
16. Shengding Hu, Yuge Tu, Xu Han, Chaoqun He, Ganqu Cui, Xiang Long, Zhi Zheng, Yewei Fang, Yuxiang Huang, Weilin Zhao, Xinrong Zhang, Zheng Leng Thai, Kaihuo Zhang, Chongyi Wang, Yuan Yao, Chenyang Zhao, Jie Zhou, Jie Cai, Zhongwu Zhai, Ning Ding, Chao Jia, Guoyang Zeng, Dahai Li, Zhiyuan Liu, and Maosong Sun. 2024. [Minicpm: Unveiling the potential of small language models with scalable training strategies](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/).
17. Pratik Joshi, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monojit Choudhury. 2020. [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://md.research.elamur.ai/free/en/papers/joshi-2020-state-fate-linguistic-diversity-inclusion/). In Proceedings of ACL.
18. Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, and Dan Roth. 2018. [Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences](https://md.research.elamur.ai/free/en/papers/khashabi-2018-looking-beyond-surface-challenge-set/). In Proceedings of NAACL-HLT.
19. Thomas Lavergne, Gilles Adda, Martine Adda-Decker, and Lori Lamel. 2014. Automatic language identity tagging on word and sentence-level in multilingual text sources: a case-study on Luxembourgish. In Proceedings of LREC. [find](https://scholar.google.com/scholar?q=Thomas+Lavergne%2C+Gilles+Adda%2C+Martine+Adda%2DDecker%2C+and+Lori+Lamel%2E+2014%2E+Automatic+language+identity+tagging+on+word+and+sentence%2Dlevel+in+multilingual+text+sources%3A+a+case%2Dstudy+on+Luxembourgish%2E+In+)
20. Hector Levesque, Ernest Davis, and Leora Morgenstern. 2012. The Winograd Schema Challenge. In Proceedings of KR. [find](https://scholar.google.com/scholar?q=Hector+Levesque%2C+Ernest+Davis%2C+and+Leora+Morgenstern%2E+2012%2E+The+Winograd+Schema+Challenge%2E+In+Proceedings+of+KR%2E)
21. Yaobo Liang, Yeyun Gong, Weizhen Bian, Nan Jiang, Guoqing Xie, Ruize Lin, Jiuhai Feng, Ruochen Xu, Wenjie Wang, Zhifang Chen, et al. 2020. [XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation](https://md.research.elamur.ai/free/en/papers/liang-2020-xglue-new-benchmark-dataset-cross/). In Proceedings of EMNLP.
22. Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023. [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/liu-2021-pre-train-prompt-predict-systematic/). ACM Computing Surveys, 55(9).
23. Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. [RoBERTa: A Robustly Optimized BERT Pretraining Approach](https://md.research.elamur.ai/free/en/papers/liu-2019-roberta-robustly-optimized-bert-pretraining/). In arXiv preprint arXiv:1907.11692. [↗](https://arxiv.org/abs/1907.11692)
24. Cedric Lothritz, Saad Ezzini, Christoph Purschke, Tegawendé François D Assise Bissyande, Jacques Klein, Isabella Olariu, Andrey Boytsov, Clement Lefebvre, and Anne Goujon. 2023. Comparing Pre-Training Schemes for Luxembourgish BERT Models. In Proceedings of KONVENS. [find](https://scholar.google.com/scholar?q=Cedric+Lothritz%2C+Saad+Ezzini%2C+Christoph+Purschke%2C+Tegawend%C3%A9+Fran%C3%A7ois+D+Assise+Bissyande%2C+Jacques+Klein%2C+Isabella+Olariu%2C+Andrey+Boytsov%2C+Clement+Lefebvre%2C+and+Anne+Goujon%2E+2023%2E+Comparing+Pre%2DTraining)
25. Alistair Plum, Laura Bernardy, and Tharindu Ranasinghe. 2026. [Do LLMs Judge Distantly Supervised Named Entity Labels Well? Constructing the JudgeWEL Dataset](https://md.research.elamur.ai/free/en/papers/plum-2026-do-llms-judge-distantly-supervised/). In Proceedings of LREC.
26. Alistair Plum, Caroline Döhmer, Emilia Milano, Anne-Marie Lutgen, and Christoph Purschke. 2024. LuxBank: The First Universal Dependency Treebank for Luxembourgish. In Proceedings of TLT. [find](https://scholar.google.com/scholar?q=Alistair+Plum%2C+Caroline+D%C3%B6hmer%2C+Emilia+Milano%2C+Anne%2DMarie+Lutgen%2C+and+Christoph+Purschke%2E+2024%2E+LuxBank%3A+The+First+Universal+Dependency+Treebank+for+Luxembourgish%2E+In+Proceedings+of+TLT%2E)
27. Alistair Plum, Tharindu Ranasinghe, and Christoph Purschke. 2025. Text Generation Models for Luxembourgish with Limited Data: A Balanced Multilingual Strategy. In Proceedings of VarDial. [find](https://scholar.google.com/scholar?q=Alistair+Plum%2C+Tharindu+Ranasinghe%2C+and+Christoph+Purschke%2E+2025%2E+Text+Generation+Models+for+Luxembourgish+with+Limited+Data%3A+A+Balanced+Multilingual+Strategy%2E+In+Proceedings+of+VarDial%2E)
28. Christoph Purschke. 2020. Attitudes Toward Multilingualism in Luxembourg. A Comparative Analysis of Online News Comments and Crowdsourced Questionnaire Data. Frontiers in AI, 3. [find](https://scholar.google.com/scholar?q=Christoph+Purschke%2E+2020%2E+Attitudes+Toward+Multilingualism+in+Luxembourg%2E+A+Comparative+Analysis+of+Online+News+Comments+and+Crowdsourced+Questionnaire+Data%2E+Frontiers+in+AI%2C+3%2E)
29. Tharindu Ranasinghe, Hansi Hettiarachchi, Nadeesha Chathurangi Naradde Vidana Pathirana, Damith Premasiri, Lasitha Uyangodage, Isuri Nanomi Arachchige, Alistair Plum, Paul Rayson, and Ruslan Mitkov. 2025. Sinhala Encoder-only Language Models and Evaluation. In Proceedings of ACL. [find](https://scholar.google.com/scholar?q=Tharindu+Ranasinghe%2C+Hansi+Hettiarachchi%2C+Nadeesha+Chathurangi+Naradde+Vidana+Pathirana%2C+Damith+Premasiri%2C+Lasitha+Uyangodage%2C+Isuri+Nanomi+Arachchige%2C+Alistair+Plum%2C+Paul+Rayson%2C+and+Ruslan+Mitkov%2E+2)
30. Tharindu Ranasinghe, Alistair Plum, Christoph Purschke, and Marcos Zampieri. 2023. Publish or Hold? Automatic Comment Moderation in Luxembourgish News Articles. In Proceedings of RANLP. [find](https://scholar.google.com/scholar?q=Tharindu+Ranasinghe%2C+Alistair+Plum%2C+Christoph+Purschke%2C+and+Marcos+Zampieri%2E+2023%2E+Publish+or+Hold%3F+Automatic+Comment+Moderation+in+Luxembourgish+News+Articles%2E+In+Proceedings+of+RANLP%2E)
31. Melissa Roemmele, Cosmin A. Bejan, and Andrew S. Gordon. 2011. Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning. In AAAI Spring Symposium on Logical Formalizations of Commonsense Reasoning. [find](https://scholar.google.com/scholar?q=Melissa+Roemmele%2C+Cosmin+A%2E+Bejan%2C+and+Andrew+S%2E+Gordon%2E+2011%2E+Choice+of+Plausible+Alternatives%3A+An+Evaluation+of+Commonsense+Causal+Reasoning%2E+In+AAAI+Spring+Symposium+on+Logical+Formalizations+of+Co)
32. Cedric Lothritz, Bertrand Lebichot, Kevin Allix, Lisa Veiber, Tegawende Bissyande, Jacques Klein, Andrey Boytsov, Clément Lefebvre, and Anne Goujon. 2022. LuxemBERT: Simple and Practical Data Augmentation in Language Model Pre-Training for Luxembourgish. In Proceedings of LREC. [find](https://scholar.google.com/scholar?q=Cedric+Lothritz%2C+Bertrand+Lebichot%2C+Kevin+Allix%2C+Lisa+Veiber%2C+Tegawende+Bissyande%2C+Jacques+Klein%2C+Andrey+Boytsov%2C+Cl%C3%A9ment+Lefebvre%2C+and+Anne+Goujon%2E+2022%2E+LuxemBERT%3A+Simple+and+Practical+Data+Augmenta)
33. Sebastian Ruder, Noah Constant, Jan Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, Junjie Hu, Dan Garrette, Graham Neubig, and Melvin Johnson. 2021. [XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/ruder-2021-xtreme-r-more-challenging-nuanced/). In Proceedings of EMNLP.
34. Anne-Marie Lutgen, Alistair Plum, Christoph Purschke, and Barbara Plank. 2025. [Neural Text Normalization for Luxembourgish Using Real-Life Variation Data](https://md.research.elamur.ai/free/en/papers/lutgen-2025-neural-text-normalization-luxembourgish-real/). In Proceedings of VarDial.
35. Tatiana Shavrina, Denis Shevelev, Alena Fenogenova, Irina Nikishina, et al. 2020. RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark. In Proceedings of EMNLP. [find](https://scholar.google.com/scholar?q=Tatiana+Shavrina%2C+Denis+Shevelev%2C+Alena+Fenogenova%2C+Irina+Nikishina%2C+et+al%2E+2020%2E+RussianSuperGLUE%3A+A+Russian+Language+Understanding+Evaluation+Benchmark%2E+In+Proceedings+of+EMNLP%2E)
36. Hyunji Hayley Park, Katherine J. Zhang, Coleman Haley, Kenneth Steimel, Han Liu, and Lane Schwartz. 2021a. [Morphology Matters: A Multilingual Language Modeling Analysis](https://md.research.elamur.ai/free/en/papers/park-2021-morphology-matters-multilingual-language-modeling/). TACL.
37. Joshgun Sirajzade, Daniela Gierschek, and Christoph Schommer. 2020. An Annotation Framework for Luxembourgish Sentiment Analysis. In Proceedings of SLTU-CCUR. [find](https://scholar.google.com/scholar?q=Joshgun+Sirajzade%2C+Daniela+Gierschek%2C+and+Christoph+Schommer%2E+2020%2E+An+Annotation+Framework+for+Luxembourgish+Sentiment+Analysis%2E+In+Proceedings+of+SLTU%2DCCUR%2E)
38. Sungjoon Park, Joongbo Shin, Yekyung Lee, Jaehyung Lee, Kichang Lee, Kyunghyun Lee, Sang-Woo Kim, and Heuiseok Kim. 2021b. KLUE: Korean Language Understanding Evaluation. In Proceedings of NAACL-HLT. [find](https://scholar.google.com/scholar?q=Sungjoon+Park%2C+Joongbo+Shin%2C+Yekyung+Lee%2C+Jaehyung+Lee%2C+Kichang+Lee%2C+Kyunghyun+Lee%2C+Sang%2DWoo+Kim%2C+and+Heuiseok+Kim%2E+2021b%2E+KLUE%3A+Korean+Language+Understanding+Evaluation%2E+In+Proceedings+of+NAACL%2DHLT%2E)
39. Natalie D. Snoeren, Martine Adda-Decker, and Gilles Adda. 2010. The Study of Writing Variants in an Under-resourced Language: Some Evidence from Mobile N-Deletion in Luxembourgish. In Proceedings of LREC. [find](https://scholar.google.com/scholar?q=Natalie+D%2E+Snoeren%2C+Martine+Adda%2DDecker%2C+and+Gilles+Adda%2E+2010%2E+The+Study+of+Writing+Variants+in+an+Under%2Dresourced+Language%3A+Some+Evidence+from+Mobile+N%2DDeletion+in+Luxembourgish%2E+In+Proceedings+of+L)
40. Fred Philippy, Shohreh Haddadan, and Siwen Guo. 2024. Forget NLI, Use a Dictionary: Zero-Shot Topic Classification for Low-Resource Languages with Application to Luxembourgish. In Proceedings of SIGUL. [find](https://scholar.google.com/scholar?q=Fred+Philippy%2C+Shohreh+Haddadan%2C+and+Siwen+Guo%2E+2024%2E+Forget+NLI%2C+Use+a+Dictionary%3A+Zero%2DShot+Topic+Classification+for+Low%2DResource+Languages+with+Application+to+Luxembourgish%2E+In+Proceedings+of+SIGUL)
41. Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, and Christopher Potts. 2013. [Recursive deep models for semantic compositionality over a sentiment treebank](https://md.research.elamur.ai/free/en/papers/socher-2013-recursive-deep-models-semantic-compositionality/). In Proceedings of EMNLP.
42. Yi Tay, Mostafa Dehghani, Dara Bahri, and Donald Metzler. 2022. [Efficient Transformers: A Survey](https://md.research.elamur.ai/free/en/papers/tay-2020-efficient-transformers-survey/). ACM Computing Surveys, 55(6).
43. Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, and Lucas Beyer. 2022. Scaling Vision Transformers. In Proceedings of CVPR. [find](https://scholar.google.com/scholar?q=Xiaohua+Zhai%2C+Alexander+Kolesnikov%2C+Neil+Houlsby%2C+and+Lucas+Beyer%2E+2022%2E+Scaling+Vision+Transformers%2E+In+Proceedings+of+CVPR%2E)
44. Rob van der Goot, Ibrahim Sharaf, Aizhan Imankulova, Ahmet Üstün, Marija Stepanović, Alan Ramponi, Siti Oryza Khairunnisa, Mamoru Komachi, and Barbara Plank. 2021. From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding. In Proceedings of NAACL-HLT. [find](https://scholar.google.com/scholar?q=Rob+van+der+Goot%2C+Ibrahim+Sharaf%2C+Aizhan+Imankulova%2C+Ahmet+%C3%9Cst%C3%BCn%2C+Marija+Stepanovic%CC%81%2C+Alan+Ramponi%2C+Siti+Oryza+Khairunnisa%2C+Mamoru+Komachi%2C+and+Barbara+Plank%2E+2021%2E+From+Masked+Language+Modeling+to+Tr)
45. Xiang Zhang, Senyu Li, Bradley Hauer, Ning Shi, and Grzegorz Kondrak. 2023. Don’t Trust ChatGPT when Your Question is not in English: A Study of Multilingual Abilities and Types of LLMs. In Proceedings of EMNLP. [find](https://scholar.google.com/scholar?q=Xiang+Zhang%2C+Senyu+Li%2C+Bradley+Hauer%2C+Ning+Shi%2C+and+Grzegorz+Kondrak%2E+2023%2E+Don%E2%80%99t+Trust+ChatGPT+when+Your+Question+is+not+in+English%3A+A+Study+of+Multilingual+Abilities+and+Types+of+LLMs%2E+In+Proceeding)
46. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. [Attention is all you need](https://md.research.elamur.ai/free/en/papers/vaswani-2017-attention-all-need/). In Proceedings of NeurIPS.
47. Alex Wang, Yada Pruksachatkun, Nikita Nangia, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019a. [SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/). In Proceedings of NeurIPS.
48. Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2019b. [GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/wang-2018-glue-multi-task-benchmark-analysis/). In Proceedings of ICLR.
49. Benjamin Warner, Antoine Chaffin, Benjamin Clavié, Orion Weller, Oskar Hallström, Said Taghadouini, Alexis Gallagher, Raja Biswas, Faisal Ladhak, Tom Aarsen, Griffin Thomas Adams, Jeremy Howard, and Iacopo Poli. 2025. [Smarter, better, faster, longer: A modern bidirectional encoder for fast, memory efficient, and long context finetuning and inference](https://md.research.elamur.ai/free/en/papers/warner-2024-smarter-better-faster-longer-modern/). In Proceedings of ACL.
50. Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, and Denny Zhou. 2022. [Chain-of-Thought Prompting Elicits Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/). In Proceedings of NeurIPS.
51. Orion Weller, Kathryn Ricci, Marc Marone, Antoine Chaffin, Dawn Lawrie, and Benjamin Van Durme. 2026. Seq vs Seq: An Open Suite of Paired Encoders and Decoders. In Proceedings of ICLR. [find](https://scholar.google.com/scholar?q=Orion+Weller%2C+Kathryn+Ricci%2C+Marc+Marone%2C+Antoine+Chaffin%2C+Dawn+Lawrie%2C+and+Benjamin+Van+Durme%2E+2026%2E+Seq+vs+Seq%3A+An+Open+Suite+of+Paired+Encoders+and+Decoders%2E+In+Proceedings+of+ICLR%2E)
52. Adina Williams, Nikita Nangia, and Samuel R. Bowman. 2018. [A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference](https://md.research.elamur.ai/free/en/papers/williams-2018-broad-coverage-challenge-corpus-sentence/). In Proceedings of NAACL-HLT.
53. Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, and Ludwig Schmidt. 2023. Stable and low-precision training for large-scale vision-language models. In Proccedings of NeurIPS. [find](https://scholar.google.com/scholar?q=Mitchell+Wortsman%2C+Tim+Dettmers%2C+Luke+Zettlemoyer%2C+Ari+Morcos%2C+Ali+Farhadi%2C+and+Ludwig+Schmidt%2E+2023%2E+Stable+and+low%2Dprecision+training+for+large%2Dscale+vision%2Dlanguage+models%2E+In+Proccedings+of+NeurIP)
54. Shijie Wu and Mark Dredze. 2019. [Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT](https://md.research.elamur.ai/free/en/papers/wu-2019-beto-bentz-becas-surprising-cross/). In Proceedings of EMNLP-IJCNLP.
55. Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019. [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://md.research.elamur.ai/free/en/papers/yang-2019-xlnet-generalized-autoregressive-pretraining-language/). In Proceedings of NeurIPS.

*Updated 2 November 2026*