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Few-Shot Learning

618 directly classified papers

Papers per year

Papers

Making Pre-trained Language Models Better Few-shot Learners ACL 2021
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning CVPR 2021
Labeled From Unlabeled: Exploiting Unlabeled Data for Few-Shot Deep HDR Deghosting CVPR 2021
Prototype Completion With Primitive Knowledge for Few-Shot Learning CVPR 2021
Few-Shot Transformation of Common Actions Into Time and Space CVPR 2021
Rectifying the Shortcut Learning of Background for Few-Shot Learning NIPS 2021
Online Meta-Learning via Learning with Layer-Distributed Memory NIPS 2021
FLEX: Unifying Evaluation for Few-Shot NLP NIPS 2021
TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation NIPS 2021
Few-Shot Segmentation via Cycle-Consistent Transformer NIPS 2021
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples NIPS 2021
On Episodes, Prototypical Networks, and Few-Shot Learning NIPS 2021
Characterizing Generalization under Out-Of-Distribution Shifts in Deep Metric Learning NIPS 2021
Solving Aspect Category Sentiment Analysis as a Text Generation Task EMNLP 2021
Multiple Heads Are Better Than One: Few-Shot Font Generation With Multiple Localized Experts ICCV 2021
Few-Shot Text Generation with Natural Language Instructions EMNLP 2021
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models EMNLP 2021
Nearest Neighbour Few-Shot Learning for Cross-lingual Classification EMNLP 2021
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation EMNLP 2021
Improving and Simplifying Pattern Exploiting Training EMNLP 2021
STraTA: Self-Training with Task Augmentation for Better Few-shot Learning EMNLP 2021
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP EMNLP 2021
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical Networks EMNLP 2021
AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples EMNLP 2021
CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP EMNLP 2021