7 citations · 18 across the 3 of their papers we have counts for
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cs.CL2019★ 6 cited
MultiFiT: Efficient Multi-lingual Language Model Fine-tuning
Julian Martin Eisenschlos, Sebastian Ruder, Piotr Czapla +3
Pretrained language models are promising particularly for low-resource languages as they only require unlabelled data. However, training existing models requires huge amounts of co…
cs.CL2019★ 5 cited
Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
Bobak Farzin, Piotr Czapla, Jeremy Howard
Our entry into the HAHA 2019 Challenge placed in the classification task and in the regression task. We describe our system and innovations, as well as comparing…