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Abstract: News text classification is crucial for efficient information acquisition and dissemination. While deep learning models, such as BERT and BiGRU, excel in accuracy for text classification, ...
BERTは 事前学習済み言語モデル (Pretrained Language Model) と呼ばれるモデルの一種で、大量のテキストで事前にモデルの学習をおこなっておくことで、様々なタスクに利用できる言語知識を獲得しています。 この言語知識を転用することで、多様なタスクについて、今までよりも少ない学習データで ...
In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...
The ECO-SAM utilizes a pre-trained BERT encoder to obtain semantic embedding of input texts and then leverages a self-attention mechanism to model the semantic correlation between emotions.
Abstract: Text classification tasks aim to comprehend and classify text content into specific classifications. This task is crucial for interpreting unstructured text, making it a foundational task in ...
Hello, I am trying to use BERT and LOVE for text classification recently. In your latest released code, I have some questions: Is the embedding vector of each word in the file love. emb generated by ...
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