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 976–1000 of 2964 papers

Title	Date	Tasks	Status
EMR Coding with Semi-Parametric Multi-Head Matching Networks	Jun 1, 2018	Few-Shot LearningGeneral Classification	—Unverified
CAM/CAD Point Cloud Part Segmentation via Few-Shot Learning	Jul 4, 2022	3D Part SegmentationFew-Shot Learning	—Unverified
AnnotatedTables: A Large Tabular Dataset with Language Model Annotations	Jun 24, 2024	AutoMLFew-Shot Learning	—Unverified
Few-Shot Classification in Unseen Domains by Episodic Meta-Learning Across Visual Domains	Dec 27, 2021	ClassificationFew-Shot Learning	—Unverified
Aspect-Based Few-Shot Learning	Dec 17, 2024	Few-Shot Learning	—Unverified
Few-shot Classification on Graphs with Structural Regularized GCNs	May 1, 2019	ClassificationFew-Shot Learning	—Unverified
Domain-Agnostic Few-Shot Classification by Learning Disparate Modulators	Sep 11, 2019	ClassificationDiversity	—Unverified
Empowering Large Language Models for Textual Data Augmentation	Apr 26, 2024	Data AugmentationDiversity	—Unverified
Few-Shot Classification with Contrastive Learning	Sep 17, 2022	ClassificationContrastive Learning	—Unverified
Few-shot Classification with Hypersphere Modeling of Prototypes	Nov 10, 2022	ClassificationFew-Shot Learning	—Unverified
SENet: A Spectral Filtering Approach to Represent Exemplars for Few-shot Learning	May 30, 2023	ClassificationFew-Shot Learning	—Unverified
Few-shot Class-incremental Learning for Classification and Object Detection: A Survey	Aug 13, 2023	class-incremental learningClass Incremental Learning	—Unverified
Empirical Evaluation of Topic Zero- and Few-Shot Learning for Stance Dissonance Detection	Nov 16, 2021	Few-Shot LearningStance Detection	—Unverified
Few-Shot Class-Incremental Learning with Non-IID Decentralized Data	Sep 18, 2024	class-incremental learningClass Incremental Learning	—Unverified
Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting	Feb 20, 2024	Few-Shot Learningnamed-entity-recognition	—Unverified
CalliffusionV2: Personalized Natural Calligraphy Generation with Flexible Multi-modal Control	Oct 3, 2024	Few-Shot Learning	—Unverified
Few-shot Continual Infomax Learning	Jan 1, 2023	Continual LearningFew-Shot Learning	—Unverified
Few-shot Continual Learning: a Brain-inspired Approach	Apr 19, 2021	Continual LearningFew-Shot Learning	—Unverified
Few-Shot Cross-Lingual TTS Using Transferable Phoneme Embedding	Jun 27, 2022	Few-Shot Learningtext-to-speech	—Unverified
EMO: Episodic Memory Optimization for Few-Shot Meta-Learning	Jun 8, 2023	Few-Shot LearningMeta-Learning	—Unverified
Deep Representation Learning with an Information-theoretic Loss	Nov 25, 2021	Anomaly DetectionFew-Shot Learning	—Unverified
Associative Adversarial Learning Based on Selective Attack	Dec 28, 2021	Adversarial RobustnessFew-Shot Learning	—Unverified
Calibrated neighborhood aware confidence measure for deep metric learning	Jun 8, 2020	Few-Shot LearningImage Retrieval	—Unverified
Active Learning Principles for In-Context Learning with Large Language Models	May 23, 2023	Active LearningDiversity	—Unverified
Embedding Space Allocation with Angle-Norm Joint Classifiers for Few-Shot Class-Incremental Learning	Nov 14, 2024	class-incremental learningClass Incremental 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