few-shot learning

Class-Discriminative Feature Embedding For Meta-Learning based Few-Shot Classification WACV 2020 COBE: Contextualized Object Embeddings from Narrated Instructional Video NeurIPS 2020 Composed Variational Natural Language Generation for Few-shot Intents EMNLP 2020 Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge IJCAI 2020 Context-Transformer: Tackling Object Confusion for Few-Shot Detection AAAI 2020 Contract Discovery: Dataset and a Few-Shot Semantic Retrieval Challenge with Competitive Baselines EMNLP 2020 Convergence of Meta-Learning with Task-Specific Adaptation over Partial Parameters NeurIPS 2020 Convolutional Conditional Neural Processes ICLR 2020 COVID-19 Surveillance through Twitter using Self-Supervised and Few Shot Learning EMNLP 2020 Cross-lingual Spoken Language Understanding with Regularized Representation Alignment EMNLP 2020 CrossTransformers: spatially-aware few-shot transfer NeurIPS 2020 CSI: A Coarse Sense Inventory for 85% Word Sense Disambiguation AAAI 2020 DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover's Distance and Structured Classifiers CVPR 2020 Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference EMNLP 2020 Diversity Transfer Network for Few-Shot Learning AAAI 2020 DLWL: Improving Detection for Lowshot Classes With Weakly Labelled Data CVPR 2020 Do We Need to Create Big Datasets to Learn a Task? EMNLP 2020 DPGN: Distribution Propagation Graph Network for Few-Shot Learning CVPR 2020 Dynamic Memory Induction Networks for Few-Shot Text Classification ACL 2020 Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection EMNLP 2020 Effective Few-Shot Classification with Transfer Learning COLING 2020 Efficient Intent Detection with Dual Sentence Encoders ACL 2020 Embodied Multimodal Multitask Learning IJCAI 2020 Emergent Communication Pretraining for Few-Shot Machine Translation COLING 2020 Enhanced Meta-Learning for Cross-Lingual Named Entity Recognition with Minimal Resources AAAI 2020