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 501–525 of 2964 papers

Title	Date	Tasks	Status	Hype
Federated Few-Shot Learning for Mobile NLP	Dec 12, 2022	Few-Shot LearningPrivacy Preserving	CodeCode Available	1
Penalty Method for Inversion-Free Deep Bilevel Optimization	Nov 8, 2019	Bilevel OptimizationData Poisoning	CodeCode Available	1
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis	Jul 10, 2024	Data AugmentationFew-Shot Learning	CodeCode Available	1
Point2Vec for Self-Supervised Representation Learning on Point Clouds	Mar 29, 2023	3D Part Segmentation3D Point Cloud Classification	CodeCode Available	1
Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes	Oct 8, 2024	ArticlesClassification	CodeCode Available	1
Point-DAE: Denoising Autoencoders for Self-supervised Point Cloud Learning	Nov 13, 2022	3D Object DetectionDecoder	CodeCode Available	1
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIs	Dec 27, 2024	EEGFew-Shot Learning	CodeCode Available	1
POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples NeurIPS 2021	Dec 1, 2021	Few-Shot Learning	CodeCode Available	1
EASY: Ensemble Augmented-Shot Y-shaped Learning: State-Of-The-Art Few-Shot Classification with Simple Ingredients	Jan 24, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Compressing Lengthy Context With UltraGist	May 26, 2024	Few-Shot Learning	CodeCode Available	1
Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest Images	May 31, 2021	Few-Shot LearningImage Classification	CodeCode Available	1
Dynamic Few-Shot Visual Learning without Forgetting	Apr 25, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data	Jun 14, 2021	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1
EASE: Unsupervised Discriminant Subspace Learning for Transductive Few-Shot Learning	Jan 1, 2022	Few-Shot Learning	CodeCode Available	1
Constellation Nets for Few-Shot Learning	Jan 1, 2021	ClusteringFew-Shot Image Classification	CodeCode Available	1
Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning	Jun 18, 2023	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1
Easter2.0: Improving convolutional models for handwritten text recognition	May 30, 2022	Data AugmentationFew-Shot Learning	CodeCode Available	1
Elaborative Rehearsal for Zero-shot Action Recognition	Aug 5, 2021	Action RecognitionFew-Shot Learning	CodeCode Available	1
Domain-Adaptive Few-Shot Learning	Mar 19, 2020	Domain AdaptationFew-Shot Learning	CodeCode Available	1
Diversified in-domain synthesis with efficient fine-tuning for few-shot classification	Dec 5, 2023	DiversityFew-Shot Image Classification	CodeCode Available	1
BOIL: Towards Representation Change for Few-shot Learning	Aug 20, 2020	Few-Shot LearningMeta-Learning	CodeCode Available	1
Domain Adaptive Few-Shot Open-Set Learning	Sep 22, 2023	cross-domain few-shot learningFew-Shot Learning	CodeCode Available	1
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal Perspective	Aug 26, 2022	Few-Shot LearningFew-Shot Object Detection	CodeCode Available	1
Discriminative Sample-Guided and Parameter-Efficient Feature Space Adaptation for Cross-Domain Few-Shot Learning	Mar 7, 2024	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1
Disentangled Feature Representation for Few-shot Image Classification	Sep 26, 2021	BenchmarkingClassification	CodeCode Available	1

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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