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 2576–2600 of 2964 papers

Title	Date	Tasks	Status
Kernel Methods in Hyperbolic Spaces	Jan 1, 2021	Few-Shot Learningimage-classification	—Unverified
KG-ECO: Knowledge Graph Enhanced Entity Correction for Query Rewriting	Feb 21, 2023	Entity RetrievalFew-Shot Learning	—Unverified
KNN Transformer with Pyramid Prompts for Few-Shot Learning	Oct 14, 2024	Few-Shot Learning	—Unverified
Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justice	Apr 17, 2025	ArticlesFew-Shot Learning	—Unverified
Knowledge-augmented Few-shot Visual Relation Detection	Mar 9, 2023	DiversityFew-Shot Learning	—Unverified
Knowledge Distillation Meets Few-Shot Learning: An Approach for Few-Shot Intent Classification Within and Across Domains	May 1, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Knowledge-Driven New Drug Recommendation	Oct 11, 2022	Few-Shot LearningMulti-Label Classification	—Unverified
Knowledge-grounded Dialog State Tracking	Oct 13, 2022	dialog state trackingFew-Shot Learning	—Unverified
Knowledge Guided Metric Learning for Few-Shot Text Classification	Apr 4, 2020	ClassificationFew-Shot Learning	—Unverified
Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition	Sep 20, 2020	Few-Shot LearningMulti-Label Image Recognition	—Unverified
L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout	Apr 8, 2019	Few-Shot LearningMeta-Learning	—Unverified
L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models	Feb 7, 2024	Few-Shot LearningIn-Context Learning	—Unverified
Labeled From Unlabeled: Exploiting Unlabeled Data for Few-Shot Deep HDR Deghosting	Jun 19, 2021	Few-Shot Learning	—Unverified
Labeled Memory Networks for Online Model Adaptation	Jul 5, 2017	Few-Shot LearningMeta-Learning	—Unverified
Label-guided Data Augmentation for Prompt-based Few Shot Learners	Jan 16, 2022	Data AugmentationFew-Shot Learning	—Unverified
LADs: Leveraging LLMs for AI-Driven DevOps	Feb 28, 2025	Few-Shot LearningRetrieval-augmented Generation	—Unverified
Language-guided Few-shot Semantic Segmentation	Nov 23, 2023	Few-Shot LearningFew-Shot Semantic Segmentation	—Unverified
Language Models are General-Purpose Interfaces	Jun 13, 2022	Causal Language ModelingFew-Shot Learning	—Unverified
Language models are weak learners	Jun 25, 2023	Few-Shot LearningLanguage Modelling	—Unverified
Language Models as Few-Shot Learner for Task-Oriented Dialogue Systems	Aug 14, 2020	Dialogue State TrackingFew-Shot Learning	—Unverified
Large Language Models: A New Approach for Privacy Policy Analysis at Scale	May 31, 2024	Few-Shot Learning	—Unverified
Large Language Models are Unreliable for Cyber Threat Intelligence	Mar 29, 2025	Few-Shot LearningZero-Shot Learning	—Unverified
Large Language Models as Computable Approximations to Solomonoff Induction	May 21, 2025	Few-Shot LearningIn-Context Learning	—Unverified
Large Language Models for Patient Comments Multi-Label Classification	Oct 31, 2024	De-identificationFew-Shot Learning	—Unverified
Large Language Models for Solving Economic Dispatch Problem	May 28, 2025	Few-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