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 126–150 of 2964 papers

Title	Date	Tasks	Status	Hype	Score
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	5
Bias-Eliminated Semantic Refinement for Any-Shot Learning	Feb 10, 2022	Few-Shot LearningGeneralized Zero-Shot Learning	CodeCode Available	1	5
DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot Learning	Jan 1, 2024	DenoisingFew-Shot Learning	CodeCode Available	1	5
Design of a Graphical User Interface for Few-Shot Machine Learning Classification of Electron Microscopy Data	Jul 21, 2021	Few-Shot LearningImage Segmentation	CodeCode Available	1	5
Better Generalized Few-Shot Learning Even Without Base Data	Nov 29, 2022	Few-Shot LearningGeneralized Few-Shot Learning	CodeCode Available	1	5
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic Segmentation	Dec 23, 2024	Few-Shot LearningFew-Shot Semantic Segmentation	CodeCode Available	1	5
Defining Benchmarks for Continual Few-Shot Learning	Apr 15, 2020	continual few-shot learningContinual Learning	CodeCode Available	1	5
Deeply Coupled Cross-Modal Prompt Learning	May 29, 2023	Domain AdaptationFew-Shot Learning	CodeCode Available	1	5
BioBERT: a pre-trained biomedical language representation model for biomedical text mining	Jan 25, 2019	Drug–drug Interaction ExtractionFew-Shot Learning	CodeCode Available	1	5
Deep Metric Learning for Open World Semantic Segmentation	Aug 10, 2021	Autonomous DrivingFew-Shot Learning	CodeCode Available	1	5
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis	Jul 10, 2024	Data AugmentationFew-Shot Learning	CodeCode Available	1	5
DETA: Denoised Task Adaptation for Few-Shot Learning	Mar 11, 2023	DenoisingFew-Shot Learning	CodeCode Available	1	5
Adversarial Feature Hallucination Networks for Few-Shot Learning	Mar 30, 2020	Data AugmentationDiversity	CodeCode Available	1	5
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning	Mar 15, 2020	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
Adversarial Feature Augmentation for Cross-domain Few-shot Classification	Aug 23, 2022	ClassificationCross-Domain Few-Shot	CodeCode Available	1	5
BECLR: Batch Enhanced Contrastive Few-Shot Learning	Feb 4, 2024	Contrastive LearningFew-Shot Image Classification	CodeCode Available	1	5
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency	Apr 16, 2025	Few-Shot LearningInteractive Segmentation	CodeCode Available	1	5
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels	Oct 11, 2019	Bayesian InferenceDomain Adaptation	CodeCode Available	1	5
Better Few-Shot Relation Extraction with Label Prompt Dropout	Oct 25, 2022	Few-Shot LearningRelation	CodeCode Available	1	5
Advancing Fine-Grained Classification by Structure and Subject Preserving Augmentation	Jun 20, 2024	Data AugmentationDiversity	CodeCode Available	1	5
GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection	Sep 12, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	1	5
Data Distributional Properties Drive Emergent In-Context Learning in Transformers	Apr 22, 2022	Few-Shot LearningIn-Context Learning	CodeCode Available	1	5
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study	Mar 6, 2020	Few-Shot LearningModel Selection	CodeCode Available	1	5
Detecting Hate Speech with GPT-3	Mar 23, 2021	Few-Shot LearningHate Speech Detection	CodeCode Available	1	5
Domain-Adaptive Few-Shot Learning	Mar 19, 2020	Domain AdaptationFew-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