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 1201–1225 of 2964 papers

Title	Date	Tasks	Status
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
Amortized Bayesian Meta-Learning	May 1, 2019	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues	Sep 23, 2023	Few-Shot Learning	—Unverified
HazardNet: Road Debris Detection by Augmentation of Synthetic Models	Mar 14, 2023	Few-Shot Learning	—Unverified
Head2HeadFS: Video-based Head Reenactment with Few-shot Learning	Mar 30, 2021	Few-Shot LearningPose Transfer	—Unverified
Dehazing Remote Sensing and UAV Imagery: A Review of Deep Learning, Prior-based, and Hybrid Approaches	May 13, 2024	Few-Shot LearningImage Dehazing	—Unverified
Adaptive Weighted Co-Learning for Cross-Domain Few-Shot Learning	Dec 6, 2023	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Growing from Exploration: A self-exploring framework for robots based on foundation models	Jan 24, 2024	Few-Shot Learning	—Unverified
Deficiency of Large Language Models in Finance: An Empirical Examination of Hallucination	Nov 27, 2023	Few-Shot LearningHallucination	—Unverified
Benchmarking Large Language Model Capabilities for Conditional Generation	Jun 29, 2023	BenchmarkingFew-Shot Learning	—Unverified
LAraBench: Benchmarking Arabic AI with Large Language Models	May 24, 2023	BenchmarkingFew-Shot Learning	—Unverified
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition	Mar 14, 2022	Activity RecognitionFew-Shot Learning	—Unverified
A Mixture-of-Experts Approach to Few-Shot Task Transfer in Open-Ended Text Worlds	May 9, 2024	Few-Shot LearningMixture-of-Experts	—Unverified
GS-PT: Exploiting 3D Gaussian Splatting for Comprehensive Point Cloud Understanding via Self-supervised Learning	Sep 8, 2024	3DGS3D Object Classification	—Unverified
Deep metric learning improves lab of origin prediction of genetically engineered plasmids	Nov 24, 2021	Few-Shot LearningMetric Learning	—Unverified
Deep Meta-Learning: Learning to Learn in the Concept Space	Feb 10, 2018	Few-Shot LearningMeta-Learning	—Unverified
BEAN: Interpretable Representation Learning with Biologically-Enhanced Artificial Neuronal Assembly Regularization	Sep 27, 2019	Few-Shot LearningRepresentation Learning	—Unverified
A MIMO Radar-Based Metric Learning Approach for Activity Recognition	Nov 2, 2021	Activity RecognitionFew-Shot Learning	—Unverified
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation	Jun 23, 2020	Autonomous VehiclesFew-Shot Learning	—Unverified
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey	Mar 15, 2023	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Deep learning based detection of collateral circulation in coronary angiographies	Jan 8, 2024	Coronary Artery SegmentationDeep Learning	—Unverified
A MIMO Radar-based Few-Shot Learning Approach for Human-ID	Oct 16, 2021	Few-Shot LearningMetric Learning	—Unverified
Adaptive Transfer Learning: a simple but effective transfer learning	Nov 22, 2021	Few-Shot LearningTransfer Learning	—Unverified
A Comprehensive Overview and Survey of Recent Advances in Meta-Learning	Apr 17, 2020	BIG-bench Machine LearningDeep 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