A Survey of Pun Generation: Datasets, Evaluations and Methodologies
Not on the map. Why?
Abstract (arXiv)
Pun generation seeks to creatively modify linguistic elements in text to produce humour or evoke double meanings. It also aims to preserve coherence and contextual appropriateness, making it useful in creative writing and entertainment across various media and contexts. Although pun generation has received considerable attention in computational linguistics, there is currently no dedicated survey that systematically reviews this specific area. To bridge this gap, this paper provides a comprehensive review of pun generation datasets and methods across different stages, including conventional approaches, deep learning techniques, and pre-trained language models. Additionally, we summarise both automated and human evaluation metrics used to assess the quality of pun generation. Finally, we discuss the research challenges and propose promising directions for future work.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 54 of its 196 references that are in the map. First posted on arXiv 7 Jul 2025.
Builds on
54 of 196 references.
References · 54
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
- 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
- 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
- 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
- 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
- 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
38 more
- 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
- 2016Improved Techniques for Training GANscited by 2,938
- 2020The Pile: An 800GB Dataset of Diverse Text for Language Modelingcited by 2,346
- 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
- 2015A Diversity-Promoting Objective Function for Neural Conversation Modelscited by 1,068
- 2022Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questionscited by 911
- 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
- 2023Baichuan 2: Open Large-scale Language Modelscited by 664
- 2020Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillationcited by 591
- 2020MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfercited by 443
- 2016SeqGAN: Sequence Generative Adversarial Nets with Policy Gradientcited by 375
- 2023Text-to-image Diffusion Models in Generative AI: A Surveycited by 264
- 2023Multimodal Deep Learningcited by 257
- 2023OpenChat: Advancing Open-source Language Models with Mixed-Quality Datacited by 250
- 2017Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluationcited by 206
- 2023Can large language models provide useful feedback on research papers? A large-scale empirical analysiscited by 195
- 2023Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Futurecited by 184
- 2023LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Proverscited by 161
- 2023Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Datacited by 119
- 2015Yara Parser: A Fast and Accurate Dependency Parsercited by 110
- 2018Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networkscited by 101
- 2023A Survey on Audio Diffusion Models: Text To Speech Synthesis and Enhancement in Generative AIcited by 68
- 2020Inducing Language-Agnostic Multilingual Representationscited by 48
- 2019ParaBank: Monolingual Bitext Generation and Sentential Paraphrasing via Lexically-constrained Neural Machine Translationcited by 38
- 2019Pun Generation with Surprisecited by 37
- 2020CLUECorpus2020: A Large-scale Chinese Corpus for Pre-training Language Modelcited by 36
- 2020Processing South Asian Languages Written in the Latin Script: the Dakshina Datasetcited by 35
- 2024Distractor Generation in Multiple-Choice Tasks: A Survey of Methods, Datasets, and Evaluationcited by 25
- 2022ExPUNations: Augmenting Puns with Keywords and Explanationscited by 21
- 2024"A good pun is its own reword": Can Large Language Models Understand Puns?cited by 21
- 2021Using Optimal Transport as Alignment Objective for fine-tuning Multilingual Contextualized Embeddingscited by 19
- 2019Pun-GAN: Generative Adversarial Network for Pun Generationcited by 18
- 2020ColBERT: Using BERT Sentence Embedding in Parallel Neural Networks for Computational Humorcited by 18
- 2013Arabizi Detection and Conversion to Arabiccited by 16
- 2020Introducing Aspects of Creativity in Automatic Poetry Generationcited by 14
- 2024Creating a Lens of Chinese Culture: A Multimodal Dataset for Chinese Pun Rebus Art Understandingcited by 11
- 2022A Unified Framework for Pun Generation with Humor Principlescited by 10
- 2015Backward and Forward Language Modeling for Constrained Sentence Generationcited by 9
50 most cited of 54 All 54 (JSON)
Built on by
Citing papers per year: 2026: 2.
2 papers.