Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines
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Abstract (arXiv)
Building datasets of creative text, such as humor, is quite challenging. We introduce FunLines, a competitive game where players edit news headlines to make them funny, and where they rate the funniness of headlines edited by others. FunLines makes the humor generation process fun, interactive, collaborative, rewarding and educational, keeping players engaged and providing humor data at a very low cost compared to traditional crowdsourcing approaches. FunLines offers useful performance feedback, assisting players in getting better over time at generating and assessing humor, as our analysis shows. This helps to further increase the quality of the generated dataset. We show the effectiveness of this data by training humor classification models that outperform a previous benchmark, and we release this dataset to the public.
Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). First posted on arXiv 5 Feb 2020.
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1; 2024: 3; 2025: 2; 2026: 2.
10 papers.
- 2023Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generationcited by 56
- 2024Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leapscited by 12
- 2025A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Modelscited by 10
- 2021Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?cited by 9
- 2024Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Modelscited by 9
- 2024Creativity in AI: Progresses and Challengescited by 7
- 2022Towards Multimodal Prediction of Spontaneous Humour: A Novel Dataset and First Resultscited by 4
- 2025KoWit-24: A Richly Annotated Dataset of Wordplay in News Headlinescited by 0
- 2026Learning to Think Like a Cartoon Captionist: Incongruity-Resolution Supervision for Multimodal Humor Understandingcited by 0
- 2026Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steeringcited by 0
- 2026Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering19 Apr 2026
- 2026Learning to Think Like a Cartoon Captionist: Incongruity-Resolution Supervision for Multimodal Humor Understanding16 Apr 2026
- 2025KoWit-24: A Richly Annotated Dataset of Wordplay in News Headlines3 Mar 2025
- 2025A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Models25 Jan 2025
- 2024Creativity in AI: Progresses and Challenges22 Oct 2024
- 2024Innovative Thinking, Infinite Humor: Humor Research of Large Language Models through Structured Thought Leaps14 Oct 2024
- 2024Getting Serious about Humor: Crafting Humor Datasets with Unfunny Large Language Models23 Feb 2024
- 2023Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation5 Dec 2023
- 2022Towards Multimodal Prediction of Spontaneous Humour: A Novel Dataset and First Results28 Sep 2022
- 2021Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?19 May 2021