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 1251–1275 of 2964 papers

Title	Date	Tasks	Status
Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification	Mar 26, 2024	Few-Shot Learningimage-classification	—Unverified
Automate Knowledge Concept Tagging on Math Questions with LLMs	Mar 26, 2024	Few-Shot LearningMath	—Unverified
Exploring the Generalization of Cancer Clinical Trial Eligibility Classifiers Across Diseases	Mar 25, 2024	Few-Shot Learning	—Unverified
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging	Mar 25, 2024	Few-Shot LearningImage Segmentation	—Unverified
A Little Leak Will Sink a Great Ship: Survey of Transparency for Large Language Models from Start to Finish	Mar 24, 2024	Few-Shot Learning	—Unverified
Cross-domain Multi-modal Few-shot Object Detection via Rich Text	Mar 24, 2024	Cross-Domain Few-ShotDomain Adaptation	CodeCode Available
Boosting Few-Shot Learning via Attentive Feature Regularization	Mar 23, 2024	Few-Shot Learning	—Unverified
Comprehensive Evaluation and Insights into the Use of Large Language Models in the Automation of Behavior-Driven Development Acceptance Test Formulation	Mar 22, 2024	Few-Shot LearningIn-Context Learning	CodeCode Available
Learning-to-Learn the Wave Angle Estimation	Mar 21, 2024	Few-Shot LearningMeta-Learning	—Unverified
Clinical information extraction for Low-resource languages with Few-shot learning using Pre-trained language models and Prompting	Mar 20, 2024	Domain AdaptationFew-Shot Learning	—Unverified
Pragmatic Competence Evaluation of Large Language Models for the Korean Language	Mar 19, 2024	Few-Shot LearningMultiple-choice	CodeCode Available
LUWA Dataset: Learning Lithic Use-Wear Analysis on Microscopic Images	Mar 19, 2024	Few-Shot Learningimage-classification	—Unverified
Towards Understanding the Relationship between In-context Learning and Compositional Generalization	Mar 18, 2024	Few-Shot LearningIn-Context Learning	—Unverified
CO3: Low-resource Contrastive Co-training for Generative Conversational Query Rewrite	Mar 18, 2024	Contrastive LearningData Augmentation	—Unverified
PARMESAN: Parameter-Free Memory Search and Transduction for Dense Prediction Tasks	Mar 18, 2024	Continual LearningFew-Shot Learning	—Unverified
Better (pseudo-)labels for semi-supervised instance segmentation	Mar 18, 2024	Few-Shot Learningimage-classification	—Unverified
Mixture-of-Prompt-Experts for Multi-modal Semantic Understanding	Mar 17, 2024	Few-Shot LearningLanguage Modelling	—Unverified
On the low-shot transferability of [V]-Mamba	Mar 15, 2024	Few-Shot LearningMamba	—Unverified
Investigating grammatical abstraction in language models using few-shot learning of novel noun gender	Mar 15, 2024	DecoderFew-Shot Learning	—Unverified
Multi-Objective Optimization Using Adaptive Distributed Reinforcement Learning	Mar 13, 2024	Cloud ComputingFew-Shot Learning	—Unverified
Segmentation of Knee Bones for Osteoarthritis Assessment: A Comparative Analysis of Supervised, Few-Shot, and Zero-Shot Learning Approaches	Mar 13, 2024	Few-Shot LearningMorphological Analysis	—Unverified
Search-based Optimisation of LLM Learning Shots for Story Point Estimation	Mar 13, 2024	Few-Shot LearningMeta-Learning	—Unverified
Agile gesture recognition for low-power applications: customisation for generalisation	Mar 12, 2024	Few-Shot LearningGesture Recognition	—Unverified
Boosting keyword spotting through on-device learnable user speech characteristics	Mar 12, 2024	Few-Shot LearningKeyword Spotting	CodeCode Available
Rethinking ASTE: A Minimalist Tagging Scheme Alongside Contrastive Learning	Mar 12, 2024	Aspect Sentiment Triplet ExtractionContrastive 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