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 1476–1500 of 2964 papers

Title	Date	Tasks	Status	Hype
Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control	Aug 3, 2022	Few-Shot LearningGaze Estimation	—Unverified	0
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model	Aug 2, 2022	Causal Language ModelingCommon Sense Reasoning	CodeCode Available	2
The Curse of Low Task Diversity: On the Failure of Transfer Learning to Outperform MAML and Their Empirical Equivalence	Aug 2, 2022	DiversityFew-Shot Learning	—Unverified	0
Few-shot Adaptation Works with UnpredicTable Data	Aug 1, 2022	Domain AdaptationFew-Shot Learning	CodeCode Available	1
Few-shot Single-view 3D Reconstruction with Memory Prior Contrastive Network	Jul 30, 2022	3D ReconstructionContrastive Learning	—Unverified	0
A Survey of Learning on Small Data: Generalization, Optimization, and Challenge	Jul 29, 2022	Active LearningContrastive Learning	—Unverified	0
Conservative Generator, Progressive Discriminator: Coordination of Adversaries in Few-shot Incremental Image Synthesis	Jul 29, 2022	Few-Shot LearningImage Generation	—Unverified	0
Boosting Point-BERT by Multi-choice Tokens	Jul 27, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	0
BeCAPTCHA-Type: Biometric Keystroke Data Generation for Improved Bot Detection	Jul 27, 2022	Few-Shot LearningVocal Bursts Type Prediction	—Unverified	0
Few-shot Learning with Class-Covariance Metric for Hyperspectral Image Classification	Jul 26, 2022	Few-Shot LearningHyperspectral Image Classification	CodeCode Available	1
Contrastive Knowledge-Augmented Meta-Learning for Few-Shot Classification	Jul 25, 2022	ClassificationDiversity	—Unverified	0
Kernel Relative-prototype Spectral Filtering for Few-shot Learning	Jul 24, 2022	Few-Shot Learning	CodeCode Available	0
Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence	Jul 22, 2022	Data AugmentationFew-Shot Learning	—Unverified	0
Rethinking Few-Shot Object Detection on a Multi-Domain Benchmark	Jul 22, 2022	Few-Shot LearningFew-Shot Object Detection	CodeCode Available	1
Language Model Cascades	Jul 21, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	2
Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning Approach	Jul 20, 2022	Few-Shot LearningMeta-Learning	CodeCode Available	1
Similarity of Pre-trained and Fine-tuned Representations	Jul 19, 2022	Domain AdaptationFew-Shot Learning	—Unverified	0
Self-Supervision Can Be a Good Few-Shot Learner	Jul 19, 2022	cross-domain few-shot learningFew-Shot Image Classification	CodeCode Available	1
On the cross-lingual transferability of multilingual prototypical models across NLU tasks	Jul 19, 2022	Few-Shot LearningMeta-Learning	—Unverified	0
STT: Soft Template Tuning for Few-Shot Adaptation	Jul 18, 2022	Few-Shot LearningLanguage Modeling	—Unverified	0
Generative Adversarial Networks Based on Transformer Encoder and Convolution Block for Hyperspectral Image Classification	Jul 16, 2022	ClassificationClassification Of Hyperspectral Images	—Unverified	0
Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain Few-Shot Facial Expression Recognition	Jul 16, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1
Cross-Domain Cross-Set Few-Shot Learning via Learning Compact and Aligned Representations	Jul 16, 2022	Few-Shot Learning	CodeCode Available	0
Segment-level Metric Learning for Few-shot Bioacoustic Event Detection	Jul 15, 2022	Event DetectionFew-Shot Learning	CodeCode Available	1
Tree Structure-Aware Few-Shot Image Classification via Hierarchical Aggregation	Jul 14, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1

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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