Duluth at SemEval-2020 Task 7: Using Surprise as a Key to Unlock Humorous Headlines
| Autor: | Yue Yin, Shuning Jin, XianE Tang, Ted Pedersen |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Computation and Language Computer science business.industry media_common.quotation_subject computer.software_genre SemEval Task (project management) Surprise Key (cryptography) Artificial intelligence Language model business Computation and Language (cs.CL) computer Natural language processing media_common Transformer (machine learning model) |
| Zdroj: | SemEval@COLING |
| DOI: | 10.18653/v1/2020.semeval-1.128 |
| Popis: | 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 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|