Few-Shot Learning

Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalization EMNLP 2020 IsOBS: An Information System for Oracle Bone Script EMNLP 2020 iTAML: An Incremental Task-Agnostic Meta-learning Approach CVPR 2020 Keyphrase Generation with GANs in Low-Resources Scenarios EMNLP 2020 Knowledge Graph Transfer Network for Few-Shot Recognition AAAI 2020 Language Models are Few-Shot Learners NeurIPS 2020 Learning Compositional Rules via Neural Program Synthesis NeurIPS 2020 Learning Fast Adaptation on Cross-Accented Speech Recognition Interspeech 2020 Learning Meta Model for Zero- and Few-Shot Face Anti-Spoofing AAAI 2020 Learning Task-aware Local Representations for Few-shot Learning IJCAI 2020 Learning to Autofocus CVPR 2020 Learning to Classify Intents and Slot Labels Given a Handful of Examples ACL 2020 Learning to Customize Model Structures for Few-shot Dialogue Generation Tasks ACL 2020 Learning to Decouple Relations: Few-Shot Relation Classification with Entity-Guided Attention and Confusion-Aware Training COLING 2020 Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction NeurIPS 2020 Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks COLING 2020 Learning to Forget for Meta-Learning CVPR 2020 Learning to Learn to Disambiguate: Meta-Learning for Few-Shot Word Sense Disambiguation EMNLP 2020 Learning to Learn Variational Semantic Memory NeurIPS 2020 Learning to Segment the Tail CVPR 2020 Leveraging Principal Parts for Morphological Inflection ACL 2020 Linear Disentangled Representations and Unsupervised Action Estimation NeurIPS 2020 ManyEnt: A Dataset for Few-shot Entity Typing COLING 2020 MATE: Plugging in Model Awareness to Task Embedding for Meta Learning NeurIPS 2020 Meta-Dataset: A Dataset of Datasets for Learning to Learn from Few Examples ICLR 2020