The Future of Natural Language Processing

Transfer Learning in Natural Language Processing (NLP): Open questions, current trends, limits, and future directions. Slides: A walk through interesting papers and research directions in late 2019, early2020 on: model size and computational efficiency, outofdomain generalization and model evaluation, finetuning and sample efficiency, common sense and inductive biases. by Thomas Wolf (Science lead at HuggingFace) HuggingFace on Twitter: