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 1201–1225 of 2964 papers

Title	Date	Tasks	Status	Hype
STUNT: Few-shot Tabular Learning with Self-generated Tasks from Unlabeled Tables	Mar 2, 2023	Few-Shot LearningMeta-Learning	CodeCode Available	1
CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping	Feb 28, 2023	3D Point Cloud ClassificationContrastive Learning	—Unverified	0
Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation	Feb 28, 2023	Few-Shot LearningMeta-Learning	CodeCode Available	0
DEff-GAN: Diverse Attribute Transfer for Few-Shot Image Synthesis	Feb 28, 2023	AttributeDiversity	CodeCode Available	0
Meta Learning to Bridge Vision and Language Models for Multimodal Few-Shot Learning	Feb 28, 2023	Few-Shot LearningMeta-Learning	CodeCode Available	1
LLaMA: Open and Efficient Foundation Language Models	Feb 27, 2023	Arithmetic ReasoningCode Generation	CodeCode Available	7
Layer Grafted Pre-training: Bridging Contrastive Learning And Masked Image Modeling For Label-Efficient Representations	Feb 27, 2023	Contrastive LearningFew-Shot Learning	CodeCode Available	1
AugGPT: Leveraging ChatGPT for Text Data Augmentation	Feb 25, 2023	Data AugmentationFew-Shot Learning	CodeCode Available	0
Pre-Finetuning for Few-Shot Emotional Speech Recognition	Feb 24, 2023	Few-Shot Learningspeech-recognition	CodeCode Available	0
Language Models are Few-shot Learners for Prognostic Prediction	Feb 24, 2023	Few-Shot LearningPrediction	—Unverified	0
Small Sample Hyperspectral Image Classification Based on the Random Patches Network and Recursive Filtering	Feb 23, 2023	ClassificationDimensionality Reduction	CodeCode Available	0
Sentence Simplification via Large Language Models	Feb 23, 2023	Few-Shot LearningSentence	CodeCode Available	0
One Fits All:Power General Time Series Analysis by Pretrained LM	Feb 23, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	2
Mask-guided BERT for Few Shot Text Classification	Feb 21, 2023	ClassificationContrastive Learning	—Unverified	0
Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention	Feb 21, 2023	Contrastive LearningFew-Shot Learning	—Unverified	0
KG-ECO: Knowledge Graph Enhanced Entity Correction for Query Rewriting	Feb 21, 2023	Entity RetrievalFew-Shot Learning	—Unverified	0
Meta-World Conditional Neural Processes	Feb 20, 2023	Few-Shot LearningHallucination	—Unverified	0
Few-shot Multimodal Multitask Multilingual Learning	Feb 19, 2023	Few-Shot LearningIn-Context Learning	—Unverified	0
DGP-Net: Dense Graph Prototype Network for Few-Shot SAR Target Recognition	Feb 19, 2023	Few-Shot Learning	—Unverified	0
Neural Attention Memory	Feb 18, 2023	Few-Shot LearningZero-shot Generalization	—Unverified	0
StyleAdv: Meta Style Adversarial Training for Cross-Domain Few-Shot Learning	Feb 18, 2023	Adversarial AttackCross-Domain Few-Shot	CodeCode Available	1
An Adaptive Plug-and-Play Network for Few-Shot Learning	Feb 18, 2023	Few-Shot Learning	—Unverified	0
Scalable Prompt Generation for Semi-supervised Learning with Language Models	Feb 18, 2023	Few-Shot LearningNatural Language Understanding	—Unverified	0
Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving	Feb 17, 2023	Autonomous DrivingFew-Shot Learning	—Unverified	0
CovidExpert: A Triplet Siamese Neural Network framework for the detection of COVID-19	Feb 17, 2023	Computed Tomography (CT)COVID-19 Diagnosis	—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