mlsanityData to 14 Oct 2026

Multi-Figurative Language Generation

arXiv 2209.01835 ↗First posted 5 Sep 2022cs.CLcited by 2

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Abstract (arXiv)

Figurative language generation is the task of reformulating a given text in the desired figure of speech while still being faithful to the original context. We take the first step towards multi-figurative language modelling by providing a benchmark for the automatic generation of five common figurative forms in English. We train mFLAG employing a scheme for multi-figurative language pre-training on top of BART, and a mechanism for injecting the target figurative information into the encoder; this enables the generation of text with the target figurative form from another figurative form without parallel figurative-figurative sentence pairs. Our approach outperforms all strong baselines. We also offer some qualitative analysis and reflections on the relationship between the different figures of speech.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 28 of its 46 references that are in the map. First posted on arXiv 5 Sep 2022.

Builds on

28 of 46 references.

References · 28

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16 more
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 0; 2026: 1.

2 papers.

  1. 2023Creative Data Generation: A Review Focusing on Text and Poetrycited by 5
  2. 2026Towards High-Level Semantic Intelligencecited by 0