---
title: "SkMTEB — paper by Suppa et al. (2026) — summary and ideas"
description: "Slovak, a West Slavic language with about 5 million speakers, had no dedicated benchmark for text embeddings. 57 references."
authors: ["Marek Suppa", "Andrej Ridzik", "Daniel Hládek", "Natália Kňažeková", "Viktória Ondrejová"]
year: 2026
venue: "Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.acl-long.2114/"
doi: "10.18653/v1/2026.acl-long.2114"
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/suppa-2026-skmteb-slovak-massive-text-embedding/"
---
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# SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation

**Authors:** [Marek Suppa](https://md.research.elamur.ai/free/en/authors/marek-suppa/), Andrej Ridzik, Daniel Hládek, Natália Kňažeková and Viktória Ondrejová · **Year:** 2026 · **Venue:** [Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/acl/) ([ACL 2026](https://md.research.elamur.ai/free/en/venues/acl/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.acl-long.2114/) · [PDF](https://aclanthology.org/2026.acl-long.2114.pdf) · [DOI 10.18653/v1/2026.acl-long.2114](https://doi.org/10.18653/v1/2026.acl-long.2114) · [OpenAlex](https://openalex.org/W7166880417)

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

## Summary
Slovak, a West Slavic language with about 5 million speakers, had no dedicated benchmark for text embeddings. MMTEB covers it with only 8 tasks, most of them slices of multilingual sets. The NLU-oriented skLEP does not test retrieval or semantic similarity.

The authors built SkMTEB, an MTEB-style suite of 31 datasets across 7 task types: retrieval, reranking, classification, clustering, STS, pair classification and bitext mining. It combines existing resources, older corpora recast for new tasks (for example, summarization data reused as retrieval) and seven newly created sets.

They evaluated 31 open and commercial embedding models. Large instruction-tuned multilingual models scored best, while Slovak encoders built for NLU worked poorly as embedders.

To get small models that run locally, they trimmed the vocabulary of Multilingual E5 and fine-tuned it on curated Slovak data. The resulting e5-sk-small and e5-sk-large perform competitively with proprietary APIs.

All resources are openly released and offer a low-cost recipe for other under-resourced languages.

## Key points
- **Coverage:** SkMTEB has 31 datasets, roughly 4× MMTEB's 8 Slovak tasks, and only 6 datasets overlap with MMTEB. Domains include news, parliament, fact-checking and pharmacy Q&A, with texts dated 2000–2025.
- **New datasets (7):** SlovakNLI, DemagogSKNLI, SlovakSumSTS, PravdaTag, PravdaURL, SlovakPharmacyDrMaxReranking and SlovakPharmacyMojaLekarenReranking.
- **Adapted models:** e5-sk-small has 45M parameters and e5-sk-large has 365M, up to 62% smaller than the originals. Each adaptation needs under one GPU-hour, and the paper includes ablations of trimming, fine-tuning and prompt use.
- **Effect of trimming:** Slovak–English and Slovak–Czech transfer stays within 1 F1 point of the original. Stated limitations are that some NLI, STS and RTE data is machine-translated and that legal and technical domains are underrepresented.
- **Release:** models and datasets are at huggingface.co/collections/slovak-nlp/skmteb, and code is at github.com/slovak-nlp/skmteb.

*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

- [Kempelen Institute of Intelligent Technologies](https://md.research.elamur.ai/free/en/ngos/kempelen-institute-of-intelligent-technologies/) — Nonprofit, Bratislava, Slovakia · 11 works · 82 citations
- [Comenius University Bratislava](https://md.research.elamur.ai/free/en/universities/comenius-university-bratislava/) — University, Bratislava, Slovakia · 2 works · 26 citations

Also on the byline: [Technical University of Košice](https://ror.org/05xm08015).

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🧭 Topics (2): [📏 Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · 1,220 works · [🌍 Multilingual & cross-lingual NLP](https://md.research.elamur.ai/free/en/topics/multilingual-nlp/) · 828 works

## Cite

Cite as: Marek Suppa, Andrej Ridzik, Daniel Hládek, Natália Kňažeková and Viktória Ondrejová. 2026. SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

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

```bibtex
@inproceedings{suppa2026skmteb,
  title = {{SkMTEB: Slovak Massive Text Embedding Benchmark and Model Adaptation}},
  author = {Marek Suppa, Andrej Ridzik, Daniel Hládek, Natália Kňažeková and Viktória Ondrejová},
  booktitle = {Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.acl-long.2114},
  url = {https://doi.org/10.18653/v1/2026.acl-long.2114}
}
```

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- [next → Slovene Morphological and Word Formation Segmentation: A Novel Dataset and Evaluation](https://md.research.elamur.ai/free/en/papers/pranjic-2026-slovene-morphological-word-formation-segmentation/)
- [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/43/)

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*Updated 1 November 2026*