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Computer Science > Computation and Language

arXiv:2209.01835 (cs)
[Submitted on 5 Sep 2022]

Title:Multi-Figurative Language Generation

Authors:Huiyuan Lai, Malvina Nissim
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Abstract: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.
Comments: Accepted to COLING 2022
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:2209.01835 [cs.CL]
  (or arXiv:2209.01835v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2209.01835

Submission history

From: Huiyuan Lai [view email]
[v1] Mon, 5 Sep 2022 08:48:09 UTC (846 KB)
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