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--- |
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language: |
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- en |
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- es |
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- fr |
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- nl |
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- de |
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- fi |
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- ru |
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- tr |
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- ko |
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- zh |
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- ja |
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- th |
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- pt |
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- it |
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- sv |
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- hu |
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- pl |
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- et |
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- hr |
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- uk |
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- el |
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- da |
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- he |
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tags: |
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- biomedical |
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- bionlp |
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- entity linking |
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- embedding |
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- bert |
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--- |
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A multilingual **BERGAMOT**: **B**iomedical **E**ntity **R**epresentation with **G**raph-**A**ugmented **M**ulti-**O**bjective **T**ransformer model with pre-trained on UMLS (version 2020AB) using a Graph Attention Network (GAT) encoder. |
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For technical details see our [NAACL 2024 paper](https://aclanthology.org/2024.findings-naacl.288). |
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[Here is the poster](https://github.com/Andoree/BERGAMOT/blob/main/BERGAMOT_poster_naacl.jpg) of our paper. |
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For pretraining code see our github: [https://github.com/Andoree/BERGAMOT](https://github.com/Andoree/BERGAMOT). |
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## Citation |
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```bibtex |
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@inproceedings{sakhovskiy-et-al-2024-bergamot, |
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title = "Biomedical Entity Representation with Graph-Augmented Multi-Objective Transformer", |
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author = "Sakhovskiy, Andrey and Semenova, Natalia and Kadurin, Artur and Tutubalina, Elena", |
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booktitle = "Findings of the Association for Computational Linguistics: NAACL 2024", |
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month = jun, |
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year = "2024", |
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address = "Mexico City, Mexico", |
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publisher = "Association for Computational Linguistics", |
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} |
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``` |
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