phanxuanphucnd / active-learning-in-nlp

Active learning in NLP

Active learning in Nature Language Processing

Reading List of Active learning by Phuc Phan © Copyright 2022.

Surveys

• A Survey of Active Learning for Natural Language Processing, 2022, [Paper]

• A Comparative Survey of Deep Active Learning, 2022, [Paper]

• A Survey of Deep Active Learning, 2020, [Paper]

• A Survey of Active Learning for Text Classification using Deep Neural Networks, 2020, [Paper]

Methodlogies

• ALLSH: Active Learning Guided by Local Sensitivity and Hardness, 2022, [Paper] [Source code]

• Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers, 2022, [Paper] [Source code]

• AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models, 2022, [Paper] [Source code]

• Active Learning for Sequence Tagging with Deep Pre-trained Models and Bayesian Uncertainty Estimates, 2021, [Paper]

• Active Learning by Acquiring Contrastive Examples, 2021, [Paper] [Source code]

• Diversity-Aware Batch Active Learning for Dependency Parsing, 2021, [Paper] [Source code]

• Deep Active Learning: Unified and Principled Method for Query and Training, 2020, [Paper] [Source code]

• Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study, 2018, [Paper] [Source code 1] [2]

• Deep Active Learning for Named Entity Recognition, 2018, [Paper]

• Dropout as a bayesian approximation: Representing model uncertainty in deep learning, 2016, [Paper] [Source code]

• Active Discriminative Text Representation Learning, 2016, [Paper]

Toolkit

• DeepAL+: Deep Active Learning Toolkit, [url]