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 1776–1800 of 2964 papers

Title	Date	Tasks	Status
Multi-Objective Few-shot Learning for Fair Classification	Oct 5, 2021	AttributeClassification	—Unverified
Multi-Objective Meta Learning	Feb 14, 2021	Domain AdaptationFew-Shot Learning	—Unverified
Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning	Mar 13, 2024	Cloud ComputingFew-Shot Learning	—Unverified
Multi-Representation Ensemble in Few-Shot Learning	Jan 1, 2021	Few-Shot Learning	—Unverified
Multi-scale Adaptive Task Attention Network for Few-Shot Learning	Nov 30, 2020	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Multi-step Estimation for Gradient-based Meta-learning	Jun 8, 2020	Few-Shot LearningMeta-Learning	—Unverified
Multi-unit soft sensing permits few-shot learning	Sep 27, 2023	Few-Shot Learning	—Unverified
Museum Exhibit Identification Challenge for Domain Adaptation and Beyond	Feb 4, 2018	Domain AdaptationFew-Shot Learning	—Unverified
Museum Exhibit Identification Challenge for the Supervised Domain Adaptation and Beyond	Sep 1, 2018	Domain AdaptationFew-Shot Learning	—Unverified
Music auto-tagging in the long tail: A few-shot approach	Sep 12, 2024	Few-Shot LearningMusic Auto-Tagging	—Unverified
Mutual CRF-GNN for Few-Shot Learning	Jun 19, 2021	Few-Shot Learning	—Unverified
Mutual Reinforcement Effects in Japanese Sentence Classification and Named Entity Recognition Tasks	Jul 18, 2023	ClassificationFew-Shot Learning	—Unverified
Naive Few-Shot Learning: Uncovering the fluid intelligence of machines	May 24, 2022	Anomaly DetectionFew-Shot Learning	—Unverified
NAVCON: A Cognitively Inspired and Linguistically Grounded Corpus for Vision and Language Navigation	Dec 17, 2024	Few-Shot LearningVision and Language Navigation	—Unverified
NDPNet: A novel non-linear data projection network for few-shot fine-grained image classification	Jun 13, 2021	Few-Shot LearningFine-Grained Image Classification	—Unverified
Negatives Make A Positive: An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning	Apr 4, 2024	Few-Shot LearningPseudo Label	—Unverified
NERIF: GPT-4V for Automatic Scoring of Drawn Models	Nov 21, 2023	Few-Shot Learning	—Unverified
Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models	Mar 4, 2025	Few-Shot LearningModel Selection	—Unverified
Neural Attention Memory	Feb 18, 2023	Few-Shot LearningZero-shot Generalization	—Unverified
Neural-Bayesian Program Learning for Few-shot Dialogue Intent Parsing	Oct 8, 2024	Feature EngineeringFew-Shot Learning	—Unverified
Neural Graph Matching Networks for Fewshot 3D Action Recognition	Sep 1, 2018	3D Action RecognitionAction Recognition	—Unverified
Neural networks that overcome classic challenges through practice	Oct 14, 2024	Few-Shot LearningSystematic Generalization	—Unverified
Neural Variational Dropout Processes	Sep 29, 2021	Few-Shot LearningImage Inpainting	—Unverified
NeurIPS'22 Cross-Domain MetaDL competition: Design and baseline results	Aug 31, 2022	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Next-item Recommendations in Short Sessions	Jul 15, 2021	Few-Shot LearningMeta-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