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 1401–1425 of 2964 papers

Title	Date	Tasks	Status
A Broad Dataset is All You Need for One-Shot Object Detection	Nov 9, 2020	AllFew-Shot Learning	—Unverified
Argumentative Stance Prediction: An Exploratory Study on Multimodality and Few-Shot Learning	Oct 11, 2023	Argument MiningFew-Shot Learning	—Unverified
A Nested Bi-level Optimization Framework for Robust Few Shot Learning	Nov 13, 2020	Few-Shot LearningMeta-Learning	—Unverified
Affinity Network Fusion and Semi-supervised Learning for Cancer Patient Clustering	May 22, 2018	ClusteringFew-Shot Learning	—Unverified
Fast visual grounding in interaction: bringing few-shot learning with neural networks to an interactive robot	Jun 1, 2020	Few-Shot LearningTransfer Learning	—Unverified
Fast Task Adaptation for Few-Shot Learning	Sep 25, 2019	Few-Shot Learning	—Unverified
Generalized Adaptation for Few-Shot Learning	Nov 25, 2019	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Fast Adaptation with Kernel and Gradient based Meta Leaning	Nov 1, 2024	Few-Shot LearningMeta-Learning	—Unverified
Clip4Retrofit: Enabling Real-Time Image Labeling on Edge Devices via Cross-Architecture CLIP Distillation	May 23, 2025	Autonomous Drivingcross-modal alignment	—Unverified
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks	Jul 2, 2020	Few-Shot LearningLearning Theory	—Unverified
Fair Few-shot Learning with Auxiliary Sets	Aug 28, 2023	FairnessFew-Shot Learning	—Unverified
FAD: Frequency Adaptation and Diversion for Cross-domain Few-shot Learning	May 13, 2025	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Clinical Risk Prediction Using Language Models: Benefits And Considerations	Nov 29, 2023	DiagnosticFew-Shot Learning	—Unverified
Facial Landmark Correlation Analysis	Nov 24, 2019	Facial Landmark DetectionFew-Shot Learning	—Unverified
FACE: Few-shot Adapter with Cross-view Fusion for Cross-subject EEG Emotion Recognition	Mar 24, 2025	Domain AdaptationEEG	—Unverified
Face Behavior a la carte: Expressions, Affect and Action Units in a Single Network	Oct 15, 2019	Emotion RecognitionFew-Shot Learning	—Unverified
EyeDAS: Securing Perception of Autonomous Cars Against the Stereoblindness Syndrome	May 13, 2022	Autonomous DrivingDecision Making	—Unverified
Are Large Language Models Good Essay Graders?	Sep 19, 2024	Automated Essay ScoringFew-Shot Learning	—Unverified
A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts	Sep 21, 2022	Few-Shot LearningHandwritten Text Recognition	—Unverified
External-Memory Networks for Low-Shot Learning of Targets in Forward-Looking-Sonar Imagery	Jul 22, 2021	Few-Shot LearningZero-Shot Learning	—Unverified
Clinical information extraction for Low-resource languages with Few-shot learning using Pre-trained language models and Prompting	Mar 20, 2024	Domain AdaptationFew-Shot Learning	—Unverified
Exploring the Space of Key-Value-Query Models with Intention	May 17, 2023	Deep LearningFew-Shot Learning	—Unverified
A Reinforcement Learning-based Offensive semantics Censorship System for Chatbots	Jul 13, 2022	ChatbotFew-Shot Learning	—Unverified
Generalizable Denoising of Microscopy Images using Generative Adversarial Networks and Contrastive Learning	Mar 27, 2023	Contrastive LearningDenoising	—Unverified
Exploring the MIT Mathematics and EECS Curriculum Using Large Language Models	Jun 15, 2023	Electrical EngineeringFew-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