The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding
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.
Cite
Text
Enevoldsen et al. "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding." Neural Information Processing Systems, 2024. doi:10.52202/079017-1276Markdown
[Enevoldsen et al. "The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding." Neural Information Processing Systems, 2024.](https://mlanthology.org/neurips/2024/enevoldsen2024neurips-scandinavian/) doi:10.52202/079017-1276BibTeX
@inproceedings{enevoldsen2024neurips-scandinavian,
title = {{The Scandinavian Embedding Benchmarks: Comprehensive Assessment of Multilingual and Monolingual Text Embedding}},
author = {Enevoldsen, Kenneth and Kardos, Márton and Muennighoff, Niklas and Nielbo, Kristoffer Laigaard},
booktitle = {Neural Information Processing Systems},
year = {2024},
doi = {10.52202/079017-1276},
url = {https://mlanthology.org/neurips/2024/enevoldsen2024neurips-scandinavian/}
}