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 1176–1200 of 2964 papers

Title	Date	Tasks	Status
Detecting Actionable Requests and Offers on Social Media During Crises Using LLMs	Apr 22, 2025	Few-Shot LearningHumanitarian	—Unverified
Beyond English: Evaluating LLMs for Arabic Grammatical Error Correction	Dec 13, 2023	Few-Shot LearningGrammatical Error Correction	—Unverified
An Adaptive Plug-and-Play Network for Few-Shot Learning	Feb 18, 2023	Few-Shot Learning	—Unverified
Gradient-Based Meta-Learning Using Uncertainty to Weigh Loss for Few-Shot Learning	Aug 17, 2022	Few-Shot LearningMeta-Learning	—Unverified
Grammatical information in BERT sentence embeddings as two-dimensional arrays	Dec 15, 2023	Few-Shot LearningSentence	—Unverified
Designing Informative Metrics for Few-Shot Example Selection	Mar 6, 2024	Few-Shot Learningfew-shot-ner	—Unverified
Beyond Deepfake Images: Detecting AI-Generated Videos	Apr 24, 2024	Face SwappingFew-Shot Learning	—Unverified
Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN	Jan 10, 2024	DiversityFew-Shot Learning	—Unverified
Beyond Data Scarcity: A Frequency-Driven Framework for Zero-Shot Forecasting	Nov 24, 2024	Few-Shot LearningSynthetic Data Generation	—Unverified
AdaptMol: Adaptive Fusion from Sequence String to Topological Structure for Few-shot Drug Discovery	May 17, 2025	Drug DiscoveryFew-Shot Learning	—Unverified
Dependable Neural Networks for Safety Critical Tasks	Dec 20, 2019	Autonomous VehiclesDomain Adaptation	—Unverified
Beyond CLIP Generalization: Against Forward&Backward Forgetting Adapter for Continual Learning of Vision-Language Models	May 12, 2025	Continual LearningFew-Shot Learning	—Unverified
Dental Severity Assessment through Few-shot Learning and SBERT Fine-tuning	Feb 24, 2024	DiagnosticFew-Shot Learning	—Unverified
Dense Classification and Implanting for Few-Shot Learning	Mar 12, 2019	ClassificationFew-Shot Learning	—Unverified
Better (pseudo-)labels for semi-supervised instance segmentation	Mar 18, 2024	Few-Shot Learningimage-classification	—Unverified
A Multi-solution Study on GDPR AI-enabled Completeness Checking of DPAs	Nov 23, 2023	Few-Shot LearningLanguage Modeling	—Unverified
GPTree: Towards Explainable Decision-Making via LLM-powered Decision Trees	Nov 13, 2024	Decision MakingFeature Engineering	—Unverified
Demystifying Prompts in Language Models via Perplexity Estimation	Dec 8, 2022	Few-Shot Learning	—Unverified
Demystification of Few-shot and One-shot Learning	Apr 25, 2021	Few-Shot LearningOne-Shot Learning	—Unverified
DemoShapley: Valuation of Demonstrations for In-Context Learning	Oct 10, 2024	FairnessFew-Shot Learning	—Unverified
AMP0: Species-Specific Prediction of Anti-microbial Peptides using Zero and Few Shot Learning	Oct 28, 2019	Few-Shot Learning	—Unverified
Benchmarking Toxic Molecule Classification using Graph Neural Networks and Few Shot Learning	Nov 22, 2023	BenchmarkingDrug Discovery	—Unverified
DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstration	Dec 6, 2021	Few-Shot LearningHuman-Object Interaction Detection	—Unverified
A Comprehensive Review of Few-shot Action Recognition	Jul 20, 2024	Action RecognitionFew-Shot action recognition	—Unverified
Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts	Jun 20, 2023	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