Few-Shot Learning

Language Models are Few-Shot Butlers EMNLP 2021 Language Models are Few-shot Multilingual Learners EMNLP 2021 Language Models for Lexical Inference in Context EACL 2021 Large-Scale Meta-Learning with Continual Trajectory Shifting ICML 2021 Learn from Concepts: Towards the Purified Memory for Few-shot Learning IJCAI 2021 Learning a Universal Template for Few-shot Dataset Generalization ICML 2021 Learning Dynamic Alignment via Meta-Filter for Few-Shot Learning CVPR 2021 Learning from Miscellaneous Other-Class Words for Few-shot Named Entity Recognition ACL 2021 Learning from My Friends: Few-Shot Personalized Conversation Systems via Social Networks AAAI 2021 Learning How to Ask: Querying LMs with Mixtures of Soft Prompts NAACL 2021 Learning Implicit Temporal Alignment for Few-shot Video Classification IJCAI 2021 Learning Intact Features by Erasing-Inpainting for Few-shot Classification AAAI 2021 Learning Normal Dynamics in Videos With Meta Prototype Network CVPR 2021 Learning Prototype Representations Across Few-Shot Tasks for Event Detection EMNLP 2021 Learning Rare Category Classifiers on a Tight Labeling Budget ICCV 2021 Learning To Count Everything CVPR 2021 Learning To Hallucinate Examples From Extrinsic and Intrinsic Supervision ICCV 2021 Learning to Learn Dense Gaussian Processes for Few-Shot Learning NeurIPS 2021 Learning with Different Amounts of Annotation: From Zero to Many Labels EMNLP 2021 `Less Than One'-Shot Learning: Learning N Classes From M < N Samples AAAI 2021 Lexicon Learning for Few Shot Sequence Modeling ACL 2021 MetaHTR: Towards Writer-Adaptive Handwritten Text Recognition CVPR 2021 Meta-Learning for Relative Density-Ratio Estimation NeurIPS 2021 Meta-Learning With Task-Adaptive Loss Function for Few-Shot Learning ICCV 2021 Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation ACL 2021