Text Classification
fastText
language-identification
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  OpenLID-v3 is a high-coverage, high-performance language identification model. It is an improved version of [OpenLID-v2](https://huggingface.co/laurievb/OpenLID-v2).
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  The original model and training data are described in [Burchell et al. (2023)](https://aclanthology.org/2023.acl-short.75/), [the OpenLID-v2 dataset repo](https://huggingface.co/datasets/laurievb/OpenLID-v2).
 
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  ### How to use
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  ### BibTeX entry and citation info
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- #### ACL citation (preferred)
 
 
 
 
 
 
 
 
 
 
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  ```
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  @inproceedings{burchell-etal-2023-open,
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  }
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  ```
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  [![arXiv](https://img.shields.io/badge/arXiv-2305.13820-b31b1b.svg)](https://arxiv.org/abs/2305.13820)
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  This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350 and from UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee [grant number 10052546].
 
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  OpenLID-v3 is a high-coverage, high-performance language identification model. It is an improved version of [OpenLID-v2](https://huggingface.co/laurievb/OpenLID-v2).
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  The original model and training data are described in [Burchell et al. (2023)](https://aclanthology.org/2023.acl-short.75/), [the OpenLID-v2 dataset repo](https://huggingface.co/datasets/laurievb/OpenLID-v2).
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+ This model is described in the [OpenLID-v3 paper](https://arxiv.org/abs/2602.13139).
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  ### How to use
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  ### BibTeX entry and citation info
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+ ```
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+ @misc{fedorova2026openlidv3improvingprecisionclosely,
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+ title={OpenLID-v3: Improving the Precision of Closely Related Language Identification -- An Experience Report},
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+ author={Mariia Fedorova and Nikolay Arefyev and Maja Buljan and Jindřich Helcl and Stephan Oepen and Egil Rønningstad and Yves Scherrer},
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+ year={2026},
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+ eprint={2602.13139},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CL},
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+ url={https://arxiv.org/abs/2602.13139},
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+ }
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+ ```
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  ```
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  @inproceedings{burchell-etal-2023-open,
 
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  }
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  ```
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+ [![arXiv](https://img.shields.io/badge/arXiv-2602.13139-b31b1b.svg)](https://arxiv.org/abs/2602.13139)
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  [![arXiv](https://img.shields.io/badge/arXiv-2305.13820-b31b1b.svg)](https://arxiv.org/abs/2305.13820)
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  This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101070350 and from UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee [grant number 10052546].