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 1401–1425 of 2964 papers

Title	Date	Tasks	Status
From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models	Jun 8, 2025	ARCFew-Shot Learning	—Unverified
Differentiable Entailment for Parameter Efficient Few Shot Learning	Jan 31, 2023	Few-Shot Learning	—Unverified
Crowdsourcing with Meta-Workers: A New Way to Save the Budget	Nov 7, 2021	Few-Shot Learningimage-classification	—Unverified
Automatic detection of rare pathologies in fundus photographs using few-shot learning	Jul 22, 2019	Few-Shot LearningOne-Shot Learning	—Unverified
Hyperspectral Imaging-Based Grain Quality Assessment With Limited Labelled Data	Nov 17, 2024	Classification Of Hyperspectral ImagesFew-Shot Learning	—Unverified
Hyperspherical embedding for novel class classification	Feb 5, 2021	ClassificationFew-Shot Learning	—Unverified
From Dataset to Real-world: General 3D Object Detection via Generalized Cross-domain Few-shot Learning	Mar 8, 2025	3D Object DetectionAutonomous Driving	—Unverified
FrLove : Could a Frenchman rapidly identify Lovecraft?	Jan 17, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Few-shot Medical Image Segmentation via Cross-Reference Transformer	Apr 19, 2023	Few-Shot LearningImage Segmentation	—Unverified
Cross-Modulation Networks for Few-Shot Learning	Dec 1, 2018	Few-Shot Learning	—Unverified
Frequency Guidance Matters in Few-Shot Learning	Jan 1, 2023	Few-Shot LearningMetric Learning	—Unverified
ICDAR 2024 Competition on Few-Shot and Many-Shot Layout Segmentation of Ancient Manuscripts (SAM)	Sep 11, 2024	DiversityDocument Layout Analysis	—Unverified
Automatic Combination of Sample Selection Strategies for Few-Shot Learning	Feb 5, 2024	Few-Shot LearningIn-Context Learning	—Unverified
Identifying Fairness Issues in Automatically Generated Testing Content	Apr 23, 2024	FairnessFew-Shot Learning	—Unverified
Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation	Oct 17, 2020	DecoderFew-Shot Learning	—Unverified
Identity Document to Selfie Face Matching Across Adolescence	Dec 20, 2019	Few-Shot LearningTriplet	—Unverified
ALLSH: Active Learning Guided by Local Sensitivity and Hardness	May 10, 2022	Active LearningFew-Shot Learning	—Unverified
Investigating Cost-Efficiency of LLM-Generated Training Data for Conversational Semantic Frame Analysis	Oct 9, 2024	Few-Shot Learning	—Unverified
Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control	Aug 3, 2022	Few-Shot LearningGaze Estimation	—Unverified
iFuzzyTL: Interpretable Fuzzy Transfer Learning for SSVEP BCI System	Oct 16, 2024	Domain AdaptationEEG	—Unverified
Cross-Modal Mapping: Mitigating the Modality Gap for Few-Shot Image Classification	Dec 28, 2024	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Cross-Modal Learning for Chemistry Property Prediction: Large Language Models Meet Graph Machine Learning	Aug 27, 2024	Few-Shot LearningProperty Prediction	—Unverified
Four Eyes Are Better Than Two: Harnessing the Collaborative Potential of Large Models via Differentiated Thinking and Complementary Ensembles	May 22, 2025	EgoSchemaFew-Shot Learning	—Unverified
Automate Knowledge Concept Tagging on Math Questions with LLMs	Mar 26, 2024	Few-Shot LearningMath	—Unverified
Automated Human Cell Classification in Sparse Datasets using Few-Shot Learning	Jul 27, 2021	ClassificationFew-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