There Once Was a Really Bad Poet, It Was Automated but You Didn't Know It
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Abstract (arXiv)
Limerick generation exemplifies some of the most difficult challenges faced in poetry generation, as the poems must tell a story in only five lines, with constraints on rhyme, stress, and meter. To address these challenges, we introduce LimGen, a novel and fully automated system for limerick generation that outperforms state-of-the-art neural network-based poetry models, as well as prior rule-based poetry models. LimGen consists of three important pieces: the Adaptive Multi-Templated Constraint algorithm that constrains our search to the space of realistic poems, the Multi-Templated Beam Search algorithm which searches efficiently through the space, and the probabilistic Storyline algorithm that provides coherent storylines related to a user-provided prompt word. The resulting limericks satisfy poetic constraints and have thematically coherent storylines, which are sometimes even funny (when we are lucky).
Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 15 of its 48 references that are in the map. First posted on arXiv 5 Mar 2021.
Builds on
15 of 48 references.
References · 15
- 2017Six Challenges for Neural Machine Translationcited by 335
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- 2016Chinese Poetry Generation with Planning based Neural Networkcited by 22
- 2018Beyond Narrative Description: Generating Poetry from Images by Multi-Adversarial Trainingcited by 17
- 2020MixPoet: Diverse Poetry Generation via Learning Controllable Mixed Latent Spacecited by 17
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Citing papers per year: 2023: 1.
1 paper.