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        <title>A Unified Framework for Pun Generation with Humor Principles</title>
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    <abstract>We propose a unified framework to generate both homophonic and homographic puns to resolve the split-up in existing works. Specifically, we incorporate three linguistic attributes of puns to the language models: ambiguity, distinctiveness, and surprise. Our framework consists of three parts: 1) a context words/phrases selector to promote the aforementioned attributes, 2) a generation model trained on non-pun sentences to incorporate the context words/phrases into the generation output, and 3) a label predictor that learns the structure of puns which is used to steer the generation model at inference time. Evaluation results on both pun types demonstrate the efficacy of our model over strong baselines.</abstract>
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%0 Conference Proceedings
%T A Unified Framework for Pun Generation with Humor Principles
%A Tian, Yufei
%A Sheth, Divyanshu
%A Peng, Nanyun
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Findings of the Association for Computational Linguistics: EMNLP 2022
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F tian-etal-2022-unified
%X We propose a unified framework to generate both homophonic and homographic puns to resolve the split-up in existing works. Specifically, we incorporate three linguistic attributes of puns to the language models: ambiguity, distinctiveness, and surprise. Our framework consists of three parts: 1) a context words/phrases selector to promote the aforementioned attributes, 2) a generation model trained on non-pun sentences to incorporate the context words/phrases into the generation output, and 3) a label predictor that learns the structure of puns which is used to steer the generation model at inference time. Evaluation results on both pun types demonstrate the efficacy of our model over strong baselines.
%R 10.18653/v1/2022.findings-emnlp.237
%U https://aclanthology.org/2022.findings-emnlp.237/
%U https://doi.org/10.18653/v1/2022.findings-emnlp.237
%P 3253-3261

Markdown (Informal)

[A Unified Framework for Pun Generation with Humor Principles](https://aclanthology.org/2022.findings-emnlp.237/) (Tian et al., Findings 2022)

• A Unified Framework for Pun Generation with Humor Principles (Tian et al., Findings 2022)

ACL

• Yufei Tian, Divyanshu Sheth, and Nanyun Peng. 2022. A Unified Framework for Pun Generation with Humor Principles. In Findings of the Association for Computational Linguistics: EMNLP 2022, pages 3253–3261, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.