1k citations · 1.1k across the 5 of their papers we have counts for
Showing 2018 · cs.CLShow all
2 papers · 2 filters
cs.CL2018★ 7 cited
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…
cs.CL2018
Universal Language Model Fine-tuning for Text Classification
Jeremy Howard, Sebastian Ruder
Inductive transfer learning has greatly impacted computer vision, but existing approaches in NLP still require task-specific modifications and training from scratch. We propose Uni…