  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.
