Yuka Yokogawa


2024

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Leveraging Plug-and-Play Models for Rhetorical Structure Control in Text Generation
Yuka Yokogawa | Tatsuya Ishigaki | Hiroya Takamura | Yusuke Miyao | Ichiro Kobayashi
Proceedings of the 17th International Natural Language Generation Conference

We propose a method that extends a BART-based language generator using a plug-and-play model to control the rhetorical structure of generated text. Our approach considers rhetorical relations between clauses and generates sentences that reflect this structure using plug-and-play language models. We evaluated our method using the Newsela corpus, which consists of texts at various levels of English proficiency. Our experiments demonstrated that our method outperforms the vanilla BART in terms of the correctness of output discourse and rhetorical structures. In existing methods, the rhetorical structure tends to deteriorate when compared to the baseline, the vanilla BART, as measured by n-gram overlap metrics such as BLEU. However, our proposed method does not exhibit this significant deterioration, demonstrating its advantage.