Thank you BART! Rewarding Pre-Trained Models Improves Formality Style Transfer

Scarcity of parallel data causes formality style transfer models to have scarce success in preserving content. We show that fine-tuning pre-trained language (GPT-2) and sequence-to-sequence (BART) models boosts content preservation, and that this is possible even with limited amounts of parallel dat...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Lai, Huiyuan, Toral, Antonio, Nissim, Malvina
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Computation and Language
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!