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 2901–2925 of 2964 papers

Title	Date	Tasks	Status
Interpolating Convolutional Neural Networks Using Batch Normalization	Sep 1, 2018	Few-Shot LearningStyle Transfer	—Unverified
Neural Graph Matching Networks for Fewshot 3D Action Recognition	Sep 1, 2018	3D Action RecognitionAction Recognition	—Unverified
Open Set Chinese Character Recognition using Multi-typed Attributes	Aug 27, 2018	AttributeFew-Shot Learning	—Unverified
Few Shot Learning with Simplex	Jul 27, 2018	Few-Shot Learning	—Unverified
Few-Shot Adaptation for Multimedia Semantic Indexing	Jul 19, 2018	Few-Shot Learningparameter estimation	—Unverified
Large Margin Few-Shot Learning	Jul 8, 2018	Few-Shot LearningGeneral Classification	—Unverified
Attention-based Few-Shot Person Re-identification Using Meta Learning	Jun 24, 2018	Few-Shot LearningMeta-Learning	—Unverified
Uncertainty in Multitask Transfer Learning	Jun 20, 2018	Few-Shot LearningTransfer Learning	—Unverified
Bilevel Programming for Hyperparameter Optimization and Meta-Learning	Jun 13, 2018	Few-Shot LearningHyperparameter Optimization	—Unverified
Delta-encoder: an effective sample synthesis method for few-shot object recognition	Jun 12, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
Probabilistic Model-Agnostic Meta-Learning	Jun 7, 2018	Active LearningFew-Shot Image Classification	—Unverified
Deep Mixture of Experts via Shallow Embedding	Jun 5, 2018	Few-Shot LearningMeta-Learning	CodeCode Available
Meta-Learner with Linear Nulling	Jun 4, 2018	ClassificationFew-Shot Learning	—Unverified
EMR Coding with Semi-Parametric Multi-Head Matching Networks	Jun 1, 2018	Few-Shot LearningGeneral Classification	—Unverified
Object-Level Representation Learning for Few-Shot Image Classification	May 28, 2018	ClassificationFew-Shot Image Classification	—Unverified
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning	May 25, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
Meta-Learning Probabilistic Inference For Prediction	May 24, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
TADAM: Task dependent adaptive metric for improved few-shot learning	May 23, 2018	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available
Affinity Network Fusion and Semi-supervised Learning for Cancer Patient Clustering	May 22, 2018	ClusteringFew-Shot Learning	—Unverified
AffinityNet: semi-supervised few-shot learning for disease type prediction	May 22, 2018	Deep LearningFew-Shot Learning	CodeCode Available
Adapted Deep Embeddings: A Synthesis of Methods for k-Shot Inductive Transfer Learning	May 22, 2018	Few-Shot LearningMetric Learning	CodeCode Available
AgileNet: Lightweight Dictionary-based Few-shot Learning	May 21, 2018	Few-Shot Learning	—Unverified
Task-Agnostic Meta-Learning for Few-shot Learning	May 20, 2018	ClassificationFew-Shot Learning	—Unverified
Diverse Few-Shot Text Classification with Multiple Metrics	May 19, 2018	ClassificationFew-Shot Learning	CodeCode Available
Siamese Capsule Networks	May 18, 2018	Face VerificationFew-Shot 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