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A multilingual BERGAMOT model with pre-trained on UMLS (version 2020AB) using a Graph Attention Network (GAT) encoder.
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The model is described in paper "Biomedical Entity Representation with Graph-Augmented Multi-Objective Transformer " which is accepted to NAACL 2024!
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For pretraining code see our github: [https://github.com/Andoree/BERGAMOT](https://github.com/Andoree/BERGAMOT).
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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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