Papers by Yijin Xiong

1 papers
Fusing Label Embedding into BERT: An Efficient Improvement for Text Classification (2021.findings-acl)

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Challenge: Existing methods to improve text classification performance of pre-trained models have been used to improve their performance.
Approach: They propose a method for improving BERT's performance by using a label embedding technique while keeping almost the same computational cost.
Outcome: The proposed method improves BERT's performance on six text classification benchmark datasets while keeping almost the same computational cost.

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