ByGPT5: End-to-End Style-conditioned Poetry Generation with Token-free Language Models

Understand

State-of-the-art poetry generation systems are often complex.

• They either consist of task-specific model pipelines, incorporate prior knowledge in the form of manually created constraints, or both.
• In contrast, end-to-end models would not suffer from the overhead of having to model prior knowledge and could learn the nuances of poetry from data alone, reducing the degree of human supervision required.
• In this work, we investigate end-to-end poetry generation conditioned on styles such as rhyme, meter, and alliteration.