학술논문

Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines
Document Type
Working Paper
Source
Subject
Computer Science - Computation and Language
Language
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.
Comment: To appear in the Proceedings of the 14th International Workshop on Semantic Evaluation (SemEval 2020), December 12-13, 2020, Barcelona