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 1601–1625 of 2964 papers

Title	Date	Tasks	Status
Few-shot Learning by Exploiting Visual Concepts within CNNs	Nov 22, 2017	Few-Shot Learning	—Unverified
Few-shot Learning by Focusing on Differences	Sep 25, 2019	ClassificationFew-Shot Learning	—Unverified
Few-Shot Learning: Expanding ID Cards Presentation Attack Detection to Unknown ID Countries	Sep 10, 2024	Few-Shot LearningMeta-Learning	—Unverified
Few-Shot Learning for Annotation-Efficient Nucleus Instance Segmentation	Feb 26, 2024	Few-shot Instance SegmentationFew-Shot Learning	—Unverified
Few-shot learning for automated content analysis: Efficient coding of arguments and claims in the debate on arms deliveries to Ukraine	Dec 28, 2023	Few-Shot LearningTask 2	—Unverified
Few-Shot Learning for Biometric Verification	Nov 12, 2022	Few-Shot Learning	—Unverified
Few-Shot Learning for Chronic Disease Management: Leveraging Large Language Models and Multi-Prompt Engineering with Medical Knowledge Injection	Jan 16, 2024	Depression DetectionFeature Engineering	—Unverified
Few-Shot Learning for Clinical Natural Language Processing Using Siamese Neural Networks	Aug 31, 2022	Deep LearningFew-Shot Learning	—Unverified
Few-shot Learning for Cross-Target Stance Detection by Aggregating Multimodal Embeddings	Jan 11, 2023	Few-Shot LearningStance Detection	—Unverified
Few-shot Learning for CT Scan based COVID-19 Diagnosis	Feb 1, 2021	Computed Tomography (CT)COVID-19 Diagnosis	—Unverified
Few-shot Learning for Domain-specific Fine-grained Image Classification	Jul 23, 2019	ClassificationFew-Shot Learning	—Unverified
Few-Shot Learning for Industrial Time Series: A Comparative Analysis Using the Example of Screw-Fastening Process Monitoring	Jun 16, 2025	BenchmarkingFew-Shot Learning	—Unverified
Few Shot Learning for Information Verification	Feb 22, 2021	ArticlesFew-Shot Learning	—Unverified
Few Shot Learning for Medical Imaging: A Comparative Analysis of Methodologies and Formal Mathematical Framework	May 8, 2023	Few-Shot LearningMedical Image Analysis	—Unverified
Few-shot learning for medical text: A systematic review	Apr 21, 2022	ArticlesFew-Shot Learning	—Unverified
Few-shot Learning for Multi-label Intent Detection	Oct 11, 2020	Few-Shot LearningIntent Detection	—Unverified
Few-Shot Learning for Road Object Detection	Jan 29, 2021	Few-Shot LearningFew-Shot Object Detection	—Unverified
Few-shot Learning for Slot Tagging with Attentive Relational Network	Mar 3, 2021	Few-Shot Learning	—Unverified
Few-shot Learning for Spatial Regression	Oct 9, 2020	Few-Shot LearningGaussian Processes	—Unverified
Few-shot Learning for Sumerian Named Entity Recognition	Jul 1, 2022	Few-Shot Learningnamed-entity-recognition	—Unverified
Few Shot Learning for the Classification of Confocal Laser Endomicroscopy Images of Head and Neck Tumors	Nov 13, 2023	Few-Shot Learning	—Unverified
Few-shot Learning for Time-series Forecasting	Sep 30, 2020	Few-Shot LearningTime Series	—Unverified
Few-shot Learning for Topic Modeling	Apr 19, 2021	Few-Shot LearningTopic Models	—Unverified
Few-shot Learning for Unsupervised Feature Selection	Jul 2, 2021	Decoderfeature selection	—Unverified
When Few-Shot Learning Meets Video Object Detection	Mar 26, 2021	Few-Shot LearningFew-Shot Video Object Detection	—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