uncertainty sampling

Understanding Compositional Data Augmentation in Typologically Diverse Morphological Inflection EMNLP 2023 Active Learning Helps Pretrained Models Learn the Intended Task NeurIPS 2022 Active Learning on Pre-trained Language Model with Task-Independent Triplet Loss AAAI 2022 AcTune: Uncertainty-Based Active Self-Training for Active Fine-Tuning of Pretrained Language Models NAACL 2022 Adapting Coreference Resolution Models through Active Learning ACL 2022 ALGES: Active Learning with Gradient Embeddings for Semantic Segmentation of Laparoscopic Surgical Images MLHC 2022 A Neural Pre-Conditioning Active Learning Algorithm to Reduce Label Complexity NeurIPS 2022 Constants Matter: The Performance Gains of Active Learning ICML 2022 Convergence of Uncertainty Sampling for Active Learning ICML 2022 GALAXY: Graph-based Active Learning at the Extreme ICML 2022 One-Bit Active Query With Contrastive Pairs CVPR 2022 Revisiting Uncertainty-based Query Strategies for Active Learning with Transformers ACL 2022 Towards Robust and Reproducible Active Learning Using Neural Networks CVPR 2022 Accountable Error Characterization NAACL 2021 ActiveEA: Active Learning for Neural Entity Alignment EMNLP 2021 Active Learning by Acquiring Contrastive Examples EMNLP 2021 Active Learning for Argument Strength Estimation EMNLP 2021 Active Testing: Sample-Efficient Model Evaluation ICML 2021 Batch Active Learning at Scale NeurIPS 2021 Influence Selection for Active Learning ICCV 2021 Phrase-level Active Learning for Neural Machine Translation EMNLP 2021 Self-Training Sampling with Monolingual Data Uncertainty for Neural Machine Translation ACL 2021 Active Learning Approaches to Enhancing Neural Machine Translation EMNLP 2020 Active Sentence Learning by Adversarial Uncertainty Sampling in Discrete Space EMNLP 2020 Adversarial Sampling for Active Learning WACV 2020