Papers by Boya Xiong

1 papers
StyleBART: Decorate Pretrained Model with Style Adapters for Unsupervised Stylistic Headline Generation (2023.findings-emnlp)

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Challenge: Existing studies on unsupervised headline generation focus on a standard dataset and mono-style corpora.
Approach: They propose an unsupervised approach for stylistic headline generation using a pretrained BART model decorated with adapters responsible for different styles.
Outcome: The proposed method separates the task of style learning and headline generation, allowing for the generation of diverse headlines with diverse styles.

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