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 451–475 of 2964 papers

Title	Date	Tasks	Status	Hype	Score
ChemEval: A Comprehensive Multi-Level Chemical Evaluation for Large Language Models	Sep 21, 2024	Few-Shot LearningInstruction Following	CodeCode Available	1	5
Few Shot Learning Framework to Reduce Inter-observer Variability in Medical Images	Aug 7, 2020	Few-Shot Learning	CodeCode Available	1	5
A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt Learning	Feb 2, 2024	Few-Shot LearningGraph Representation Learning	CodeCode Available	1	5
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks	May 17, 2023	DiversityFew-Shot Learning	CodeCode Available	1	5
Clinical-Longformer and Clinical-BigBird: Transformers for long clinical sequences	Jan 27, 2022	Clinical KnowledgeDocument Classification	CodeCode Available	1	5
ClinicalMamba: A Generative Clinical Language Model on Longitudinal Clinical Notes	Mar 9, 2024	Few-Shot LearningLanguage Modeling	CodeCode Available	1	5
Meta-SGD: Learning to Learn Quickly for Few-Shot Learning	Jul 31, 2017	Few-Shot LearningMeta-Learning	CodeCode Available	1	5
CLIP2Point: Transfer CLIP to Point Cloud Classification with Image-Depth Pre-training	Oct 3, 2022	3D Point Cloud ClassificationContrastive Learning	CodeCode Available	1	5
CLIP2Scene: Towards Label-efficient 3D Scene Understanding by CLIP	Jan 12, 2023	3D Semantic SegmentationContrastive Learning	CodeCode Available	1	5
Few-Shot Learning with a Strong Teacher	Jul 1, 2021	Few-Shot LearningMeta-Learning	CodeCode Available	1	5
Context-Transformer: Tackling Object Confusion for Few-Shot Detection	Mar 16, 2020	DiversityFew-Shot Learning	CodeCode Available	1	5
Metric Based Few-Shot Graph Classification	Jun 8, 2022	ClassificationData Augmentation	CodeCode Available	1	5
Context-enriched molecule representations improve few-shot drug discovery	Apr 24, 2023	Drug DiscoveryFew-Shot Learning	CodeCode Available	1	5
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification	Aug 19, 2021	Causal Inferencecounterfactual	CodeCode Available	1	5
Model-Agnostic Few-Shot Open-Set Recognition	Jun 18, 2022	Few-Shot Learningmodel	CodeCode Available	1	5
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	Mar 9, 2017	Category-Agnostic Pose EstimationFew-Shot Image Classification	CodeCode Available	1	5
Consistency-guided Prompt Learning for Vision-Language Models	Jun 1, 2023	Domain GeneralizationFew-Shot Learning	CodeCode Available	1	5
CLUES: Few-Shot Learning Evaluation in Natural Language Understanding	Nov 4, 2021	Few-Shot LearningNatural Language Understanding	CodeCode Available	1	5
Artistic Glyph Image Synthesis via One-Stage Few-Shot Learning	Oct 11, 2019	Few-Shot LearningImage Generation	CodeCode Available	1	5
MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs	May 26, 2025	ArticlesFew-Shot Learning	CodeCode Available	1	5
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search	Nov 3, 2020	Domain AdaptationFew-Shot Learning	CodeCode Available	1	5
AdapterHub Playground: Simple and Flexible Few-Shot Learning with Adapters	Aug 18, 2021	Few-Shot LearningTransfer Learning	CodeCode Available	1	5
Constellation Nets for Few-Shot Learning	Jan 1, 2021	ClusteringFew-Shot Image Classification	CodeCode Available	1	5
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning	Mar 17, 2022	Few-Shot LearningMeta-Learning	CodeCode Available	1	5
Graph Information Aggregation Cross-Domain Few-Shot Learning for Hyperspectral Image Classification	Jun 30, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1	5

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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