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 1451–1475 of 2964 papers

Title	Date	Tasks	Status
cross-modal knowledge enhancement mechanism for few-shot learning	Jan 1, 2021	Few-Shot LearningMeta-Learning	—Unverified
Improving Instruct Models for Free: A Study on Partial Adaptation	Apr 15, 2025	Few-Shot LearningIn-Context Learning	—Unverified
Improving out-of-distribution generalization via multi-task self-supervised pretraining	Mar 30, 2020	Adversarial RobustnessDomain Generalization	—Unverified
Improving Recall of Large Language Models: A Model Collaboration Approach for Relational Triple Extraction	Apr 15, 2024	Few-Shot Learning	—Unverified
FoMo: A Foundation Model for Mobile Traffic Forecasting with Diffusion Model	Oct 20, 2024	Contrastive LearningFew-Shot Learning	—Unverified
A Contrastive Self-Supervised Learning scheme for beat tracking amenable to few-shot learning	Nov 6, 2024	Beat TrackingFew-Shot Learning	—Unverified
Cross-Modality Multi-Atlas Segmentation Using Deep Neural Networks	Aug 15, 2020	Few-Shot LearningImage Registration	—Unverified
Improving Textless Spoken Language Understanding with Discrete Units as Intermediate Target	May 29, 2023	Automatic Speech RecognitionAutomatic Speech Recognition (ASR)	—Unverified
Knowledge Guided Metric Learning for Few-Shot Text Classification	Apr 4, 2020	ClassificationFew-Shot Learning	—Unverified
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning	Sep 17, 2021	Data AugmentationFew-Shot Learning	—Unverified
Cross-Modal Few-Shot Learning with Second-Order Neural Ordinary Differential Equations	Dec 20, 2024	Few-Shot LearningImage Augmentation	—Unverified
Cross-Modal Few-Shot Learning: a Generative Transfer Learning Framework	Oct 14, 2024	Few-Shot LearningTransfer Learning	—Unverified
Diversity Over Quantity: A Lesson From Few Shot Relation Classification	Dec 6, 2024	DiversityFew-Shot Learning	—Unverified
Automated Few-Shot Time Series Forecasting based on Bi-level Programming	Mar 7, 2022	Decision MakingFew-Shot Learning	—Unverified
In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models	Dec 20, 2022	Few-Shot LearningIn-Context Learning	—Unverified
Adaptive Poincaré Point to Set Distance for Few-Shot Classification	Dec 3, 2021	Few-Shot Learning	—Unverified
In-Context Learning for Few-Shot Molecular Property Prediction	Oct 13, 2023	Few-Shot LearningIn-Context Learning	—Unverified
Flexibly Scaling Large Language Models Contexts Through Extensible Tokenization	Jan 15, 2024	Few-Shot LearningLanguage Modeling	—Unverified
Incremental Few-Shot Learning via Implanting and Compressing	Mar 19, 2022	Few-Shot Learningimage-classification	—Unverified
Incremental few-shot learning via vector quantization in deep embedded space	Jan 1, 2021	class-incremental learningClass Incremental Learning	—Unverified
Probing Few-Shot Generalization with Attributes	Dec 10, 2020	AttributeFew-Shot Learning	—Unverified
Flexible and Scalable Deep Dendritic Spiking Neural Networks with Multiple Nonlinear Branching	Dec 9, 2024	Few-Shot LearningGPU	—Unverified
Incremental Few-Shot Object Detection	Mar 10, 2020	Few-Shot LearningFew-Shot Object Detection	—Unverified
Inductive Linear Probing for Few-shot Node Classification	Jun 14, 2023	ClassificationFew-Shot Learning	—Unverified
FLEURS-R: A Restored Multilingual Speech Corpus for Generation Tasks	Aug 12, 2024	Few-Shot Learningtext-to-speech	—Unverified

Show:10 25 50

← PrevPage 59 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