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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 276–300 of 2964 papers

Title	Date	Tasks	Status	Hype
Towards Evaluating Large Language Models for Graph Query Generation	Nov 13, 2024	Few-Shot LearningKnowledge Graphs	—Unverified	0
GPTree: Towards Explainable Decision-Making via LLM-powered Decision Trees	Nov 13, 2024	Decision MakingFeature Engineering	—Unverified	0
CoCoP: Enhancing Text Classification with LLM through Code Completion Prompt	Nov 13, 2024	ClassificationCode Completion	—Unverified	0
The Surprising Effectiveness of Test-Time Training for Few-Shot Learning	Nov 11, 2024	ARCFew-Shot Learning	CodeCode Available	3
Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI	Nov 11, 2024	Data IntegrationFew-Shot Learning	CodeCode Available	0
Layer-Wise Feature Metric of Semantic-Pixel Matching for Few-Shot Learning	Nov 10, 2024	Few-Shot Learning	CodeCode Available	0
Clustering Algorithms and RAG Enhancing Semi-Supervised Text Classification with Large LLMs	Nov 9, 2024	ClassificationClustering	—Unverified	0
Selecting Between BERT and GPT for Text Classification in Political Science Research	Nov 7, 2024	Few-Shot LearningPrompt Engineering	—Unverified	0
Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot Learning	Nov 6, 2024	DiversityFew-Shot Learning	—Unverified	0
A Contrastive Self-Supervised Learning scheme for beat tracking amenable to few-shot learning	Nov 6, 2024	Beat TrackingFew-Shot Learning	—Unverified	0
Quantum Diffusion Models for Few-Shot Learning	Nov 6, 2024	DenoisingFew-Shot Learning	—Unverified	0
Leveraging Vision-Language Models for Manufacturing Feature Recognition in CAD Designs	Nov 5, 2024	Few-Shot LearningHallucination	—Unverified	0
Graph-DPEP: Decomposed Plug and Ensemble Play for Few-Shot Document Relation Extraction with Graph-of-Thoughts Reasoning	Nov 5, 2024	Document-level Relation ExtractionFew-Shot Learning	—Unverified	0
Meta-Exploiting Frequency Prior for Cross-Domain Few-Shot Learning	Nov 3, 2024	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified	0
Fast Adaptation with Kernel and Gradient based Meta Leaning	Nov 1, 2024	Few-Shot LearningMeta-Learning	—Unverified	0
Emoji Attack: A Method for Misleading Judge LLMs in Safety Risk Detection	Nov 1, 2024	Few-Shot Learning	CodeCode Available	1
Large Language Models for Patient Comments Multi-Label Classification	Oct 31, 2024	De-identificationFew-Shot Learning	—Unverified	0
FewVS: A Vision-Semantics Integration Framework for Few-Shot Image Classification	Oct 28, 2024	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation	Oct 28, 2024	Ensemble LearningFew-Shot Learning	—Unverified	0
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery	Oct 28, 2024	Drug DiscoveryFew-Shot Learning	—Unverified	0
Video to Video Generative Adversarial Network for Few-shot Learning Based on Policy Gradient	Oct 28, 2024	Deep Reinforcement LearningFew-Shot Learning	—Unverified	0
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models	Oct 28, 2024	Few-Shot LearningMMLU	CodeCode Available	1
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness	Oct 27, 2024	Domain GeneralizationFew-Shot Learning	CodeCode Available	0
Prompt Diffusion Robustifies Any-Modality Prompt Learning	Oct 26, 2024	Computational EfficiencyDomain Generalization	—Unverified	0
Vulnerability of LLMs to Vertically Aligned Text Manipulations	Oct 26, 2024	ClassificationFew-Shot Learning	—Unverified	0

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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