Few-Shot Learning

How Fine-Tuning Allows for Effective Meta-Learning NeurIPS 2021 Hypercorrelation Squeeze for Few-Shot Segmentation ICCV 2021 IEPT: Instance-Level and Episode-Level Pretext Tasks for Few-Shot Learning ICLR 2021 Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning ICLR 2021 Improve Unsupervised Pretraining for Few-Label Transfer ICCV 2021 Improving and Simplifying Pattern Exploiting Training EMNLP 2021 Improving Compositional Generalization in Classification Tasks via Structure Annotations ACL 2021 Improving Few-Shot Learning Using Composite Rotation Based Auxiliary Task WACV 2021 Improving Zero and Few-Shot Abstractive Summarization with Intermediate Fine-tuning and Data Augmentation NAACL 2021 Incentive-Aware PAC Learning AAAI 2021 Incremental few-shot learning via vector quantization in deep embedded space ICLR 2021 Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System NAACL 2021 Information theoretic meta learning with Gaussian processes UAI 2021 Integrating Pre-trained Model into Rule-based Dialogue Management AAAI 2021 Intriguing Properties of Vision Transformers NeurIPS 2021 “It doesn’t look good for a date”: Transforming Critiques into Preferences for Conversational Recommendation Systems EMNLP 2021 Iterative Label Cleaning for Transductive and Semi-Supervised Few-Shot Learning ICCV 2021 It’s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners NAACL 2021 Kernel Methods in Hyperbolic Spaces ICCV 2021 Knowledge Guided Metric Learning for Few-Shot Text Classification NAACL 2021 Known unknowns: Learning novel concepts using reasoning-by-elimination UAI 2021 Labeled From Unlabeled: Exploiting Unlabeled Data for Few-Shot Deep HDR Deghosting CVPR 2021 Language Models are Few-Shot Butlers EMNLP 2021 Language Models are Few-shot Multilingual Learners EMNLP 2021 Large-Scale Meta-Learning with Continual Trajectory Shifting ICML 2021