few-shot learning

Temporal Relation based Attentive Prototype Network for Few-shot Action Recognition ACML 2021 TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restyling ACL 2021 Theoretical bounds on estimation error for meta-learning ICLR 2021 The Role of Global Labels in Few-Shot Classification and How to Infer Them NeurIPS 2021 The Sample Complexity of Meta Sparse Regression AISTATS 2021 The Task Specification Problem CoRL 2021 Think Big, Teach Small: Do Language Models Distil Occam’s Razor? NeurIPS 2021 TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation NeurIPS 2021 Towards Contextual Learning in Few-Shot Object Classification WACV 2021 Towards Enabling Meta-Learning from Target Models NeurIPS 2021 Towards Fair Cross-Domain Adaptation via Generative Learning WACV 2021 Towards Faster and Stabilized GAN Training for High-fidelity Few-shot Image Synthesis ICLR 2021 Towards Few-shot Fact-Checking via Perplexity NAACL 2021 Towards Learning Spatially Discriminative Feature Representations ICCV 2021 Towards more equitable question answering systems: How much more data do you need? ACL 2021 Towards Offensive Language Identification for Dravidian Languages EACL 2021 Towards Realistic Few-Shot Relation Extraction EMNLP 2021 Towards robust episodic meta-learning UAI 2021 Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue Systems EMNLP 2021 Towards Zero-Shot Learning With Fewer Seen Class Examples WACV 2021 Transductive Few-Shot Classification on the Oblique Manifold ICCV 2021 Transformation Invariant Few-Shot Object Detection CVPR 2021 TransPrompt: Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification EMNLP 2021 True Few-Shot Learning with Language Models NeurIPS 2021 TuringAdvice: A Generative and Dynamic Evaluation of Language Use NAACL 2021