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In this paper, a BERT representation learning method based on medical entity features is proposed, namely EF-BERT (Entity-Feature BERT).
Data Discretized Representation based ... In this paper, a BERT representation learning method based on medical entity features is proposed, namely EF-BERT.
Apr 5, 2024 � By harnessing the bidirectional context understanding of BERT, this model excels at capturing subtle language nuances, resulting in more precise�...
Dec 20, 2022 � Bidirectional Encoder Representation from Transformer or BERT is a language model that's very popular within the NLP domain.
Feb 24, 2024 � I'm trying to develop a Tweet classifier using the BERT model ( bert-base-uncased , BertForSequenceClassification ).
Missing: Discretized Entity
This position paper puts forward our opinion on the role of discrete and continuous representations and their processing in the deep learning field.
Sep 12, 2019 � Our work shows that BERT-based models have achieved state-of-the-art performance for biomedical and clinical entity normalization.
High-quality vector representation with rich feature information can guarantee the quality of entity recognition and other downstream tasks in the field of�...
Contrastive learning has been used to learn a high-quality representation of the image in computer vision. However, contrastive learn-.
May 31, 2022 � Gao, Zheng, and Zhao. (2021) proposed a BERT-BiLSTM-CRF model and validated its feature extraction capability on the downstream NER task. 2.2.
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