Few-Shot Learning

Few-Shot Learning is an example of meta-learning, where a learner is trained on several related tasks, during the meta-training phase, so that it can generalize well to unseen (but related) tasks with just few examples, during the meta-testing phase. An effective approach to the Few-Shot Learning problem is to learn a common representation for various tasks and train task specific classifiers on top of this representation.

Source: Penalty Method for Inversion-Free Deep Bilevel Optimization

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2201–2225 of 2964 papers

Title	Date	Tasks	Status
Unbiased Max-Min Embedding Classification for Transductive Few-Shot Learning: Clustering and Classification Are All You Need	Mar 28, 2025	AllClassification	—Unverified
Uncertainty-Aware Few-Shot Image Classification	Oct 9, 2020	ClassificationFew-Shot Image Classification	—Unverified
Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion	Mar 7, 2024	Few-Shot LearningGraph Neural Network	—Unverified
Uncertainty-based Network for Few-shot Image Classification	May 17, 2022	ClassificationFew-Shot Image Classification	—Unverified
Uncertainty in Model-Agnostic Meta-Learning using Variational Inference	Jul 27, 2019	BIG-bench Machine LearningClassification	—Unverified
Uncertainty in Multitask Transfer Learning	Jun 20, 2018	Few-Shot LearningTransfer Learning	—Unverified
Understanding Benign Overfitting in Gradient-Based Meta Learning	Jun 27, 2022	Few-Shot LearningLearning Theory	—Unverified
Understanding Few-Shot Multi-Task Representation Learning Theory	Jan 17, 2022	Few-Shot LearningLearning Theory	—Unverified
Understanding In-context Learning of Addition via Activation Subspaces	May 8, 2025	Few-Shot LearningIn-Context Learning	—Unverified
Understanding the Cross-Domain Capabilities of Video-Based Few-Shot Action Recognition Models	Jun 3, 2024	Action RecognitionCross-Domain Few-Shot	—Unverified
UniAP: Towards Universal Animal Perception in Vision via Few-shot Learning	Aug 19, 2023	DecoderDiversity	—Unverified
UniPredict: Large Language Models are Universal Tabular Classifiers	Oct 5, 2023	Few-Shot Learning	—Unverified
Unknown Presentation Attack Detection against Rational Attackers	Oct 4, 2020	Few-Shot Learning	—Unverified
Unleashing In-context Learning of Autoregressive Models for Few-shot Image Manipulation	Dec 2, 2024	DiversityFew-Shot Learning	—Unverified
Unleashing the Potential of CNNs for Interpretable Few-Shot Learning	Jan 1, 2018	Few-Shot Learning	—Unverified
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps	Oct 7, 2022	Few-Shot LearningLinear evaluation	—Unverified
Unsupervised Few Shot Learning via Self-supervised Training	Sep 25, 2019	Few-Shot LearningPerson Re-Identification	—Unverified
Unsupervised Few-shot Learning via Self-supervised Training	Dec 20, 2019	BIG-bench Machine LearningClustering	—Unverified
Unsupervised Law Article Mining based on Deep Pre-Trained Language Representation Models with Application to the Italian Civil Code	Dec 2, 2021	ArticlesAttribute	—Unverified
Unsupervised Meta-Learning For Few-Shot Image Classification	Nov 28, 2018	ClassificationFew-Shot Image Classification	—Unverified
Unsupervised Task Design to Meta-Train Medical Image Classifiers	Jul 17, 2019	ClassificationFew-Shot Learning	—Unverified
Unsupervised Transfer Learning with Self-Supervised Remedy	Jun 8, 2020	ClusteringDomain Adaptation	—Unverified
UoB\_UK at SemEval 2021 Task 2: Zero-Shot and Few-Shot Learning for Multi-lingual and Cross-lingual Word Sense Disambiguation.	Aug 1, 2021	Few-Shot LearningTask 2	—Unverified
Use Me Wisely: AI-Driven Assessment for LLM Prompting Skills Development	Mar 4, 2025	feature selectionFew-Shot Learning	—Unverified
User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data	May 8, 2025	Federated LearningFew-Shot Learning	—Unverified

Show:10 25 50

← PrevPage 89 of 119Next →

All datasets MedConceptsQA DTD FGVC-Aircraft Mini-ImageNet - 5-Shot Learning Mini-Imagenet 5-way (1-shot)Stanford Cars Mini-ImageNet - 1-Shot Learning PubMedQA Caltech101 CaseHOLD EuroSAT Flowers-102

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	gpt-4-0125-preview	Accuracy	61.91	—	Unverified
2	gpt-4-0125-preview	Accuracy	52.49	—	Unverified
3	gpt-3.5-turbo	Accuracy	41.48	—	Unverified
4	gpt-3.5-turbo	Accuracy	37.06	—	Unverified
5	johnsnowlabs/JSL-MedMNX-7B	Accuracy	25.63	—	Unverified
6	yikuan8/Clinical-Longformer	Accuracy	25.55	—	Unverified
7	BioMistral/BioMistral-7B-DARE	Accuracy	25.06	—	Unverified
8	yikuan8/Clinical-Longformer	Accuracy	25.04	—	Unverified
9	PharMolix/BioMedGPT-LM-7B	Accuracy	24.92	—	Unverified
10	PharMolix/BioMedGPT-LM-7B	Accuracy	24.75	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	67.27	—	Unverified
2	SaSPA + CAL	4-shot Accuracy	48.3	—	Unverified
3	Real-Guidance + CAL	4-shot Accuracy	41.5	—	Unverified
4	CAL	4-shot Accuracy	40.9	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SaSPA + CAL	Harmonic mean	52.2	—	Unverified
2	CAL	Harmonic mean	35.2	—	Unverified
3	Variational Prompt Tuning	Harmonic mean	34.69	—	Unverified
4	Real-Guidance + CAL	Harmonic mean	34.5	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BGNN	Accuracy	92.7	—	Unverified
2	TIM-GD	Accuracy	87.4	—	Unverified
3	UNEM-Gaussian	Accuracy	66.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	EASY (transductive)	Accuracy	82.75	—	Unverified
2	HCTransformers	5 way 1~2 shot	74.74	—	Unverified
3	HyperShot	Accuracy	53.18	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SaSPA + CAL	4-shot Accuracy	66.7	—	Unverified
2	Real-Guidance + CAL	4-shot Accuracy	44.3	—	Unverified
3	CAL	4-shot Accuracy	42.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	HCTransformers	Acc	74.74	—	Unverified
2	DPGN	Acc	67.6	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	MetaGen Blended RAG (zero-shot)	Accuracy	77.9	—	Unverified
2	CoT-T5-11B (1024 Shot)	Accuracy	73.42	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	96.44	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CoT-T5-11B (1024 Shot)	Accuracy	68.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	77.71	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	81.12	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	91.57	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CovidExpert	AUC-ROC	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CoT-T5-11B (1024 Shot)	Accuracy	78.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UNEM-Gaussian	Accuracy	65.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UNEM-Gaussian	Accuracy	73.2	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	96.82	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	73.07	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	78.51	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UNEM-Gaussian	Accuracy	52.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Variational Prompt Tuning	Harmonic mean	79	—	Unverified