3 papers
cs.CL2020
AxCell: Automatic Extraction of Results from Machine Learning Papers
Marcin Kardas, Piotr Czapla, Pontus Stenetorp +4
Tracking progress in machine learning has become increasingly difficult with the recent explosion in the number of papers. In this paper, we present AxCell, an automatic machine le…
cs.CL2019
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.CL2018
Universal Language Model Fine-Tuning with Subword Tokenization for Polish
Piotr Czapla, Jeremy Howard, Marcin Kardas
Universal Language Model for Fine-tuning [arXiv:1801.06146] (ULMFiT) is one of the first NLP methods for efficient inductive transfer learning. Unsupervised pretraining results in…