🙏 If you are able to, please help me fund my open research. 🙏 Thank you for your generosity! 🤗 FremyCompany/BioLORD 2023 This model was trained using BioLORD, a new pre training strategy for producing meaningful representations for clinical sentences and biomedical concepts. State of the art methodologies operate by maximizing the similarity in representation of names referring to the same concept, and preventing collapse through contrastive learning. However, because biomedical names are not always self explanatory, it sometimes results in non semantic representations. BioLORD overcomes this issue by grounding its concept representations using definitions, as well as short descriptions derived from a multi relational knowledge graph consisting of biomedical ontologies. Thanks to this grounding, our model produces more semantic concept representations that match more closely the hierarchical structure of ontologies. BioLORD 2023 establishes a new state of the art for text similarity on both clinical sentences (MedSTS) and biomedical concepts (EHR Rel B). This model is based on sentence transformers/all mpnet base v2 and was further finetuned on the BioLORD Dataset and LLM genera…
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