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

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Showing 1051–1075 of 2964 papers

Title	Date	Tasks	Status
Fine-Grain Few-Shot Vision via Domain Knowledge as Hyperspherical Priors	May 23, 2020	ClassificationFew-Shot Learning	—Unverified
EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing	Apr 30, 2022	Few-Shot LearningKnowledge Distillation	—Unverified
Brain-inspired global-local learning incorporated with neuromorphic computing	Jun 5, 2020	Continual LearningFew-Shot Learning	—Unverified
Early-Stopping for Meta-Learning: Estimating Generalization from the Activation Dynamics	Sep 29, 2021	Few-Shot LearningMeta-Learning	—Unverified
Fine-Grained Few Shot Learning with Foreground Object Transformation	Sep 13, 2021	Data AugmentationFew-Shot Learning	—Unverified
Dynamic Memory Induction Networks for Few-Shot Text Classification	May 12, 2020	ClassificationFew-Shot Learning	—Unverified
Dynamic Input Structure and Network Assembly for Few-Shot Learning	Aug 22, 2017	Few-Shot Learning	—Unverified
Advancing Video Anomaly Detection: A Concise Review and a New Dataset	Feb 7, 2024	Anomaly DetectionDiversity	—Unverified
Fine-grained Few-shot Recognition by Deep Object Parsing	Jul 14, 2022	Few-Shot LearningObject	—Unverified
Dynamic Few-Shot Learning for Knowledge Graph Question Answering	Jul 1, 2024	Few-Shot LearningGraph Question Answering	—Unverified
Dynamic Context-Aware Prompt Recommendation for Domain-Specific AI Applications	Jun 25, 2025	Few-Shot Learning	—Unverified
Language Models are Few-shot Learners for Prognostic Prediction	Feb 24, 2023	Few-Shot LearningPrediction	—Unverified
Fine-grained Image-to-Image Transformation towards Visual Recognition	Jan 12, 2020	Few-Shot LearningFine-Grained Image Recognition	—Unverified
First Train to Generate, then Generate to Train: UnitedSynT5 for Few-Shot NLI	Dec 12, 2024	Data AugmentationDiversity	—Unverified
FLAT: Few-Shot Learning via Autoencoding Transformation Regularizers	Dec 29, 2019	Data AugmentationFew-Shot Learning	—Unverified
FungiTastic: A multi-modal dataset and benchmark for image categorization	Aug 24, 2024	ClassificationFew-Shot Learning	—Unverified
Dynamic Conditional Networks for Few-Shot Learning	Sep 1, 2018	Face GenerationFew-Shot Learning	—Unverified
Boosting Transductive Few-Shot Fine-Tuning With Margin-Based Uncertainty Weighting and Probability Regularization	Jan 1, 2023	Few-Shot Learning	—Unverified
Advances in MetaDL: AAAI 2021 challenge and workshop	Feb 1, 2022	Few-Shot Learning	—Unverified
Dual Context-Guided Continuous Prompt Tuning for Few-Shot Learning	May 1, 2022	Few-Shot Learning	—Unverified
Dual-channel Prototype Network for few-shot Classification of Pathological Images	Nov 14, 2023	ClassificationDiagnostic	—Unverified
FGN: Fully Guided Network for Few-Shot Instance Segmentation	Mar 31, 2020	Few-shot Instance SegmentationFew-Shot Learning	—Unverified
Dual Adversarial Alignment for Realistic Support-Query Shift Few-shot Learning	Sep 5, 2023	Few-Shot Learning	—Unverified
Boosting Supervision with Self-Supervision for Few-shot Learning	Jun 17, 2019	Few-Shot LearningSelf-Supervised Learning	—Unverified
DrugLLM: Open Large Language Model for Few-shot Molecule Generation	May 7, 2024	Drug DesignDrug Discovery	—Unverified

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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