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Augmenting Poetry Composition with Verse by Verse

arXiv 2103.17205 ↗First posted 31 Mar 2021cs.CLcited by 5

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Abstract (arXiv)

We describe Verse by Verse, our experiment in augmenting the creative process of writing poetry with an AI. We have created a group of AI poets, styled after various American classic poets, that are able to offer as suggestions generated lines of verse while a user is composing a poem. In this paper, we describe the underlying system to offer these suggestions. This includes a generative model, which is tasked with generating a large corpus of lines of verse offline and which are then stored in an index, and a dual-encoder model that is tasked with recommending the next possible set of verses from our index given the previous line of verse.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 9 of its 24 references that are in the map. First posted on arXiv 31 Mar 2021.

Builds on

9 of 24 references.

References · 9

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processingcited by 1,973
  3. 2017Efficient Natural Language Response Suggestion for Smart Replycited by 228
  4. 2020Investigating Societal Biases in a Poetry Composition Systemcited by 47
  5. 2020TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restylingcited by 39
  6. 2018Deep-speare: A Joint Neural Model of Poetic Language, Meter and Rhymecited by 35
  7. 2015Quantization based Fast Inner Product Searchcited by 29
  8. 2015DopeLearning: A Computational Approach to Rap Lyrics Generationcited by 17
  9. 2019GPT-based Generation for Classical Chinese Poetrycited by 12

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Cited by year

Citing papers per year: 2021: 1; 2022: 2; 2023: 0; 2024: 2.

5 papers.