mlsanityData to 14 Oct 2026

Rhyme-aware Chinese lyric generator based on GPT

arXiv 2408.10130 ↗First posted 19 Aug 2024cs.CL cs.AIcited by 10

Not on the map. Why?

Abstract (arXiv)

Neural language representation models such as GPT, pre-trained on large-scale corpora, can effectively capture rich semantic patterns from plain text and be fine-tuned to consistently improve natural language generation performance. However, existing pre-trained language models used to generate lyrics rarely consider rhyme information, which is crucial in lyrics. Using a pre-trained model directly results in poor performance. To enhance the rhyming quality of generated lyrics, we incorporate integrated rhyme information into our model, thereby improving lyric generation performance.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 7 of its 8 references that are in the map. First posted on arXiv 19 Aug 2024.

Builds on

7 of 8 references.

References · 7

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2023GPT-4 Technical Reportcited by 18,396
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  5. 2019ERNIE: Enhanced Language Representation with Informative Entitiescited by 528
  6. 2017Flexible and Creative Chinese Poetry Generation Using Neural Memorycited by 9
  7. 2024LIVE: Learnable In-Context Vector for Visual Question Answeringcited by 5

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 6; 2025: 3; 2026: 1.

10 papers.