Papers by Houwei Chou

1 papers
Developing Prefix-Tuning Models for Hierarchical Text Classification (2022.emnlp-industry)

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Challenge: Hierarchical text classification (HTC) is a key task in many industrial applications. Pre-trained Language Models (PLMs) have become dominant for most natural language processing (NLP) tasks.
Approach: They investigate how prefix tuning can improve hierarchical text classification . prefix-tuning model only needs less than 1% of parameters to achieve performance .
Outcome: The proposed model can achieve comparable performance to regular full fine-tuning.

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