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 2601–2625 of 2964 papers

Title	Date	Tasks	Status
Meta-Meta Classification for One-Shot Learning	Apr 17, 2020	ClassificationFew-Shot Learning	CodeCode Available
Revisiting Few-Shot Learning from a Causal Perspective	Sep 28, 2022	DiversityFew-Shot Learning	CodeCode Available
High-order structure preserving graph neural network for few-shot learning	May 29, 2020	Few-Shot LearningGraph Neural Network	CodeCode Available
TADAM: Task dependent adaptive metric for improved few-shot learning	May 23, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
Hierarchy-based Image Embeddings for Semantic Image Retrieval	Sep 26, 2018	Few-Shot LearningImage Retrieval	CodeCode Available
ACE: Anatomically Consistent Embeddings in Composition and Decomposition	Jan 17, 2025	Few-Shot LearningImage Cropping	CodeCode Available
Hierarchical Variational Memory for Few-shot Learning Across Domains	Dec 15, 2021	Few-Shot LearningVariational Inference	CodeCode Available
Revisiting In-context Learning Inference Circuit in Large Language Models	Oct 6, 2024	Few-Shot LearningIn-Context Learning	CodeCode Available
Metaphor Detection for Low Resource Languages: From Zero-Shot to Few-Shot Learning in Middle High German	Jun 1, 2022	Few-Shot LearningWord Embeddings	CodeCode Available
Deep Mixture of Experts via Shallow Embedding	Jun 5, 2018	Few-Shot LearningMeta-Learning	CodeCode Available
TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning	Apr 11, 2019	AttributeFew-Shot Learning	CodeCode Available
Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning	Mar 28, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
PACIA: Parameter-Efficient Adapter for Few-Shot Molecular Property Prediction	Oct 1, 2023	Few-Shot LearningGraph Neural Network	CodeCode Available
Hidden Entity Detection from GitHub Leveraging Large Language Models	Jan 8, 2025	Few-Shot Learningnamed-entity-recognition	CodeCode Available
Boosting the Generalization Capability in Cross-Domain Few-shot Learning via Noise-enhanced Supervised Autoencoder	Aug 11, 2021	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available
Hebbian and Gradient-based Plasticity Enables Robust Memory and Rapid Learning in RNNs	Feb 7, 2023	Few-Shot Learning	CodeCode Available
An Open-set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic Environments	Feb 26, 2020	Face RecognitionFew-Shot Learning	CodeCode Available
Meta-ticket: Finding optimal subnetworks for few-shot learning within randomly initialized neural networks	May 31, 2022	Few-Shot LearningMeta-Learning	CodeCode Available
TAPE: Assessing Few-shot Russian Language Understanding	Oct 23, 2022	Adversarial AttackAdversarial Text	CodeCode Available
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient’s Perspective	Jun 1, 2022	Binary ClassificationFew-Shot Learning	CodeCode Available
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property Prediction	Feb 4, 2023	Few-Shot LearningMolecular Docking	CodeCode Available
Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive Study	Jan 14, 2024	Deep LearningDepression Detection	CodeCode Available
Cross-lingual Approaches for the Detection of Adverse Drug Reactions in German from a Patient's Perspective	Aug 3, 2022	Binary ClassificationFew-Shot Learning	CodeCode Available
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning	May 16, 2019	Few-Shot LearningMeta-Learning	CodeCode Available
GSHOT: Few-shot Generative Modeling of Labeled Graphs	Jun 6, 2023	Drug DiscoveryFew-Shot Learning	CodeCode Available

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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