Generalized Few-Shot Learning
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Benchmarks
Most implemented
Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions
Learning Adaptive Classifiers Synthesis for Generalized Few-Shot Learning
Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
Better Generalized Few-Shot Learning Even Without Base Data
Papers
MetaChest: Generalized few-shot learning of pathologies from chest X-rays
The limited availability of annotated data presents a major challenge for applying deep learning methods to medical image analysis. Few-shot learning methods aim to recognize new classes from only a small number of label…
Generalized Few-Shot LearningMulti-Label ClassificationTransfer LearningImproving Few-shot Generalization of Safety Classifiers via Data Augmented Parameter-Efficient Fine-Tuning
As large language models (LLMs) are widely adopted, new safety issues and policies emerge, to which existing safety classifiers do not generalize well. If we have only observed a few examples of violations of a new safet…
Data AugmentationFew-Shot LearningGeneralized Few-Shot Learningparameter-efficient fine-tuningBetter Generalized Few-Shot Learning Even Without Base Data
This paper introduces and studies zero-base generalized few-shot learning (zero-base GFSL), which is an extreme yet practical version of few-shot learning problem. Motivated by the cases where base data is not available …
Few-Shot LearningGeneralized Few-Shot LearningImpossible Triangle: What's Next for Pre-trained Language Models?
Recent development of large-scale pre-trained language models (PLM) have significantly improved the capability of models in various NLP tasks, in terms of performance after task-specific fine-tuning and zero-shot / few-s…
Data AugmentationFew-Shot LearningGeneralized Few-Shot LearningKnowledge Distillation+1Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection
Intent Detection is one of the core tasks of dialog systems. Few-shot Intent Detection is challenging due to limited number of annotated utterances for novel classes. Generalized Few-shot intent detection is more realist…
Few-Shot LearningGeneralized Few-Shot LearningGoal-Oriented DialogIntent Detection+3Dynamic Semantic Matching and Aggregation Network for Few-shot Intent Detection
Few-shot Intent Detection is challenging due to the scarcity of available annotated utterances. Although recent works demonstrate that multi-level matching plays an important role in transferring learned knowledge from s…
Few-Shot LearningGeneralized Few-Shot LearningIntent Detection