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 101–125 of 2964 papers

Title	Date	Tasks	Status	Hype
SpectrumFM: A Foundation Model for Intelligent Spectrum Management	May 2, 2025	Anomaly DetectionFew-Shot Learning	CodeCode Available	1
KAN or MLP? Point Cloud Shows the Way Forward	Apr 18, 2025	Few-Shot LearningKolmogorov-Arnold Networks	CodeCode Available	1
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency	Apr 16, 2025	Few-Shot LearningInteractive Segmentation	CodeCode Available	1
Bridging Molecular Graphs and Large Language Models	Mar 5, 2025	Few-Shot Learning	CodeCode Available	1
Mixmamba-fewshot: mamba and attention mixer-based method with few-shot learning for bearing fault diagnosis	Feb 27, 2025	ClassificationDiagnostic	CodeCode Available	1
Cross-domain Few-shot Object Detection with Multi-modal Textual Enrichment	Feb 23, 2025	Cross-Domain Few-ShotCross-Domain Few-Shot Object Detection	CodeCode Available	1
Code Summarization Beyond Function Level	Feb 23, 2025	Code SummarizationFew-Shot Learning	CodeCode Available	1
TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data	Feb 22, 2025	Bayesian InferenceFew-Shot Learning	CodeCode Available	1
Holistic Semantic Representation for Navigational Trajectory Generation	Jan 6, 2025	Few-Shot LearningZero-Shot Learning	CodeCode Available	1
Generalization-Enhanced Few-Shot Object Detection in Remote Sensing	Jan 5, 2025	Few-Shot LearningFew-Shot Object Detection	CodeCode Available	1
ImagineFSL: Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot Learning	Jan 1, 2025	Few-Shot LearningImage Generation	CodeCode Available	1
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIs	Dec 27, 2024	EEGFew-Shot Learning	CodeCode Available	1
Neural Conformal Control for Time Series Forecasting	Dec 24, 2024	Conformal PredictionFew-Shot Learning	CodeCode Available	1
AFANet: Adaptive Frequency-Aware Network for Weakly-Supervised Few-Shot Semantic Segmentation	Dec 23, 2024	Few-Shot LearningFew-Shot Semantic Segmentation	CodeCode Available	1
MVREC: A General Few-shot Defect Classification Model Using Multi-View Region-Context	Dec 22, 2024	ClassificationFew-Shot Instance Classification	CodeCode Available	1
Text and Image Are Mutually Beneficial: Enhancing Training-Free Few-Shot Classification with CLIP	Dec 16, 2024	Few-Shot Learning	CodeCode Available	1
DiffCLIP: Few-shot Language-driven Multimodal Classifier	Dec 10, 2024	Few-Shot Learning	CodeCode Available	1
KNN-MMD: Cross Domain Wireless Sensing via Local Distribution Alignment	Dec 6, 2024	Action ClassificationAction Classification (1-shot)	CodeCode Available	1
Expanding Event Modality Applications through a Robust CLIP-Based Encoder	Dec 4, 2024	Few-Shot LearningObject Recognition	CodeCode Available	1
FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification	Nov 22, 2024	DiagnosticFew-Shot Learning	CodeCode Available	1
Exploring Foundation Models Fine-Tuning for Cytology Classification	Nov 22, 2024	ClassificationFew-Shot Learning	CodeCode Available	1
Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning	Nov 15, 2024	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1
Emoji Attack: A Method for Misleading Judge LLMs in Safety Risk Detection	Nov 1, 2024	Few-Shot Learning	CodeCode Available	1
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models	Oct 28, 2024	Few-Shot LearningMMLU	CodeCode Available	1
FewVS: A Vision-Semantics Integration Framework for Few-Shot Image Classification	Oct 28, 2024	Few-Shot Image ClassificationFew-Shot Learning	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