mlsanityData to 14 Oct 2026

Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction

arXiv 1907.03187 ↗First posted 6 Jul 2019cs.CLcited by 1

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Abstract (arXiv)

Our entry into the HAHA 2019 Challenge placed 3rd in the classification task and 2nd in the regression task. We describe our system and innovations, as well as comparing our results to a Naive Bayes baseline. A large Twitter based corpus allowed us to train a language model from scratch focused on Spanish and transfer that knowledge to our competition model. To overcome the inherent errors in some labels we reduce our class confidence with label smoothing in the loss function. All the code for our project is included in a GitHub repository for easy reference and to enable replication by others.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 6 Jul 2019.

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