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Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines

2020/09/06 by Shuning Jin, Yue Yin, Jin, Shuning +5
Computer Science · Psychology · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Humor Studies and Applications #Language, Metaphor, and Cognition #Sentiment Analysis and Opinion Mining

paper · pdf · doi:10.48550/arxiv.2009.02795

openalex publication_date 2020/09/06 · openalex created_date 2020/09/11 · openalex updated_date 2026/07/28

Abstract

We use pretrained transformer-based language models in SemEval-2020 Task 7: Assessing the Funniness of Edited News Headlines. Inspired by the incongruity theory of humor, we use a contrastive approach to capture the surprise in the edited headlines. In the official evaluation, our system gets 0.531 RMSE in Subtask 1, 11th among 49 submissions. In Subtask 2, our system gets 0.632 accuracy, 9th among 32 submissions.

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