mlsanityData to 7 Oct 2026

Stimulating Creativity with FunLines: A Case Study of Humor Generation in Headlines

arXiv 2002.02031 ↗First posted 5 Feb 2020cs.AI cs.CLcited by 10

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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.