The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding

Kenneth C. Enevoldsen, Márton Kardos, Niklas Muennighoff, Kristoffer Laigaard Nielbo
6/1/2024

No official code found. Best implementation: embeddings-benchmark/mteb (3,466 stars, Apache-2.0, last commit 2026-04-29). 1 more below.

Abstract

The evaluation of English text embeddings has transitioned from evaluating a handful of datasets to broad coverage across many tasks through benchmarks such as MTEB. However, this is not the case for multilingual text embeddings due to a lack of available benchmarks. To address this problem, we introduce the Scandinavian Embedding Benchmark (SEB). SEB is a comprehensive framework that enables text embedding evaluation for Scandinavian languages across 24 tasks, 10 subtasks, and 4 task categories. Building on SEB, we evaluate more than 26 models, uncovering significant performance disparities between public and commercial solutions not previously captured by MTEB. We open-source SEB and integrate it with MTEB, thus bridging the text embedding evaluation gap for Scandinavian languages.

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Code Implementations(2)

Apache-2.0

MTEB: Massive Text Embedding Benchmark

3,466733Shell, PythonApr 5, 20225 months agoApache-2.0
benchmarkbitext-miningclusteringinformation-retrievallow-resource-nlp+12 more
MIT

A Scandinavian Benchmark for sentence embeddings

459Python, MakefileJul 28, 202310 months agoMIT
benchmarklow-resource-nlpnatural-language-processingnlpscandinavian

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Cite this paper

@article{enevoldsen2024scandinavian,
  title  = {The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding},
  author = {Kenneth C. Enevoldsen and Márton Kardos and Niklas Muennighoff and Kristoffer Laigaard Nielbo},
  year   = {2024},
  eprint = {2406.02396},
  archivePrefix = {arXiv},
  doi    = {10.48550/arXiv.2406.02396},
  url    = {https://arxiv.org/abs/2406.02396},
  journal = {NEURIPS 2024 2024}
}

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