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 1426–1450 of 2964 papers

Title	Date	Tasks	Status
Exploring the LLM Journey from Cognition to Expression with Linear Representations	May 27, 2024	Few-Shot Learning	—Unverified
CLEAN-EVAL: Clean Evaluation on Contaminated Large Language Models	Nov 15, 2023	Few-Shot Learning	—Unverified
Are Few-shot Learning Benchmarks Too Simple ?	Sep 25, 2019	ClassificationFew-Shot Learning	—Unverified
Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers Across Diseases	Mar 25, 2024	Few-Shot Learning	—Unverified
CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion	Feb 22, 2024	Contrastive LearningFew-Shot Learning	—Unverified
Exploring the Capabilities of LLMs for IMU-based Fine-grained Human Activity Understanding	Apr 2, 2025	Activity RecognitionFew-Shot Learning	—Unverified
Exploring structure diversity in atomic resolution microscopy with graph neural networks	Oct 23, 2024	DiversityFew-Shot Learning	—Unverified
Class-Specific Channel Attention for Few-Shot Learning	Sep 3, 2022	Few-Shot Classification and SegmentationFew-Shot Image Classification	—Unverified
Exploring Sentiment Dynamics and Predictive Behaviors in Cryptocurrency Discussions by Few-Shot Learning with Large Language Models	Sep 4, 2024	Decision MakingFew-Shot Learning	—Unverified
Exploring representation learning for flexible few-shot tasks	Jan 1, 2021	Few-Shot LearningRepresentation Learning	—Unverified
Exploring Prompt-based Few-shot Learning for Grounded Dialog Generation	Sep 14, 2021	Few-Shot Learning	—Unverified
Class Interference Regularization	Sep 4, 2020	Face VerificationFew-Shot Learning	—Unverified
Class-Incremental Few-Shot Event Detection	Apr 2, 2024	Event DetectionFew-Shot Learning	—Unverified
Are Fewer Labels Possible for Few-shot Learning?	Dec 10, 2020	ClusteringFew-Shot Learning	—Unverified
AdaptAgent: Adapting Multimodal Web Agents with Few-Shot Learning from Human Demonstrations	Nov 20, 2024	Few-Shot LearningMeta-Learning	—Unverified
A Closer Look at Benchmarking Self-Supervised Pre-training with Image Classification	Jul 16, 2024	BenchmarkingFew-Shot Learning	—Unverified
Evolution imposes an inductive bias that alters and accelerates learning dynamics	May 15, 2025	Few-Shot LearningInductive Bias	—Unverified
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning	Feb 6, 2024	Few-Shot Learningimage-classification	—Unverified
Exploring internal representation of self-supervised networks: few-shot learning abilities and comparison with human semantics and recognition of objects	Apr 29, 2025	Contrastive LearningFew-Shot Learning	—Unverified
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study	Nov 21, 2023	Data AugmentationFew-Shot Learning	—Unverified
Exploring Generative AI Techniques in Government: A Case Study	Apr 6, 2025	Few-Shot LearningManagement	—Unverified
Class Imbalance in Few-Shot Learning	Jan 1, 2021	Few-Shot Learning	—Unverified
AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing	Jun 11, 2023	Few-Shot Learning	—Unverified
Exploring Factual Entailment with NLI: A News Media Study	Jun 24, 2024	ArticlesFew-Shot Learning	—Unverified
Exploring Example Selection for Few-shot Text-to-SQL Semantic Parsing	Jan 16, 2022	Few-Shot LearningIn-Context 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