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Augmented Bio-SBERT: Improving Performance for Pairwise Sentence Tasks in Bio-medical Domain
One of the modern challenges in AI is the access to high-quality and annotated data, especially in NLP; that is why augmentation is gaining importance.
No means ‘No’; a non-im-proper modeling approach, with embedded speculative context
Through this paper, we investigate various bio model’s embeddings(BioBERT, BioE- LECTRA, PubMedBERT) on their understanding of "negation and speculation context" wherein we found that these models were unable to differentiate "negated context" vs "non-negated context".
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