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 2401–2425 of 2964 papers

Title	Date	Tasks	Status
Flexibly Scaling Large Language Models Contexts Through Extensible Tokenization	Jan 15, 2024	Few-Shot LearningLanguage Modeling	—Unverified
FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning	Sep 17, 2021	Data AugmentationFew-Shot Learning	—Unverified
FoMo: A Foundation Model for Mobile Traffic Forecasting with Diffusion Model	Oct 20, 2024	Contrastive LearningFew-Shot Learning	—Unverified
FontTransformer: Few-shot High-resolution Chinese Glyph Image Synthesis via Stacked Transformers	Oct 12, 2022	Few-Shot LearningFont Generation	—Unverified
FORML: A Riemannian Hessian-free Method for Meta-learning on Stiefel Manifolds	Feb 28, 2024	Few-Shot LearningMeta-Learning	—Unverified
Four Eyes Are Better Than Two: Harnessing the Collaborative Potential of Large Models via Differentiated Thinking and Complementary Ensembles	May 22, 2025	EgoSchemaFew-Shot Learning	—Unverified
Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control	Aug 3, 2022	Few-Shot LearningGaze Estimation	—Unverified
Frequency Guidance Matters in Few-Shot Learning	Jan 1, 2023	Few-Shot LearningMetric Learning	—Unverified
FrLove : Could a Frenchman rapidly identify Lovecraft?	Jan 17, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
From Dataset to Real-world: General 3D Object Detection via Generalized Cross-domain Few-shot Learning	Mar 8, 2025	3D Object DetectionAutonomous Driving	—Unverified
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models	Jun 8, 2025	ARCFew-Shot Learning	—Unverified
From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems	Oct 1, 2024	Computational EfficiencyData Augmentation	—Unverified
From Parameters to Prompts: Understanding and Mitigating the Factuality Gap between Fine-Tuned LLMs	May 29, 2025	Few-Shot LearningIn-Context Learning	—Unverified
From Random to Informed Data Selection: A Diversity-Based Approach to Optimize Human Annotation and Few-Shot Learning	Jan 24, 2024	DiversityFew-Shot Learning	—Unverified
From User Preferences to Optimization Constraints Using Large Language Models	Mar 27, 2025	Few-Shot Learning	—Unverified
A Systematic Evaluation and Benchmark for Embedding-Aware Generative Models: Features, Models, and Any-shot Scenarios	Feb 8, 2023	Few-Shot LearningZero-Shot Learning	—Unverified
FS-HGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography	Nov 11, 2020	Domain AdaptationFew-Shot Learning	—Unverified
FSL-HDnn: A 5.7 TOPS/W End-to-end Few-shot Learning Classifier Accelerator with Feature Extraction and Hyperdimensional Computing	Sep 17, 2024	ClusteringFew-Shot Learning	—Unverified
FS-SS: Few-Shot Learning for Fast and Accurate Spike Sorting of High-channel Count Probes	Mar 23, 2025	Few-Shot LearningMeta-Learning	—Unverified
Fully Fine-tuned CLIP Models are Efficient Few-Shot Learners	Jul 4, 2024	Domain GeneralizationFew-Shot Learning	—Unverified
Function Contrastive Learning of Transferable Representations	Sep 28, 2020	Contrastive LearningFew-Shot Learning	—Unverified
Function Contrastive Learning of Transferable Meta-Representations	Oct 14, 2020	Contrastive LearningDecoder	—Unverified
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification	Apr 26, 2022	Few-Shot LearningMeta-Learning	—Unverified
FungiTastic: A multi-modal dataset and benchmark for image categorization	Aug 24, 2024	ClassificationFew-Shot Learning	—Unverified
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning	Sep 23, 2020	Few-Shot Learning	—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