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 2526–2550 of 2964 papers

Title	Date	Tasks	Status
Inconsistent Few-Shot Relation Classification via Cross-Attentional Prototype Networks with Contrastive Learning	Oct 13, 2021	Contrastive LearningFew-Shot Learning	—Unverified
In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models	Dec 20, 2022	Few-Shot LearningIn-Context Learning	—Unverified
In-Context Learning for Few-Shot Molecular Property Prediction	Oct 13, 2023	Few-Shot LearningIn-Context Learning	—Unverified
Incremental Few-Shot Learning via Implanting and Compressing	Mar 19, 2022	Few-Shot Learningimage-classification	—Unverified
Incremental few-shot learning via vector quantization in deep embedded space	Jan 1, 2021	class-incremental learningClass Incremental Learning	—Unverified
Incremental Few-Shot Meta-Learning via Indirect Discriminant Alignment	Aug 1, 2020	Few-Shot LearningIncremental Learning	—Unverified
Incremental Few-Shot Object Detection	Mar 10, 2020	Few-Shot LearningFew-Shot Object Detection	—Unverified
Inductive Linear Probing for Few-shot Node Classification	Jun 14, 2023	ClassificationFew-Shot Learning	—Unverified
Infinite Mixture Prototypes for Few-Shot Learning	Feb 12, 2019	ClusteringFew-Shot Learning	—Unverified
Inflated Episodic Memory With Region Self-Attention for Long-Tailed Visual Recognition	Jun 1, 2020	Few-Shot LearningLong-tail Learning	—Unverified
Influential Prototypical Networks for Few Shot Learning: A Dermatological Case Study	Nov 1, 2021	Domain AdaptationFew-Shot Learning	—Unverified
Information Extraction from Documents: Question Answering vs Token Classification in real-world setups	Apr 21, 2023	ClassificationFew-Shot Learning	—Unverified
Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning	Sep 3, 2021	AttributeFew-Shot Learning	—Unverified
Injecting Text and Cross-lingual Supervision in Few-shot Learning from Self-Supervised Models	Oct 10, 2021	Few-Shot Learning	—Unverified
In-Memory Nearest Neighbor Search with FeFET Multi-Bit Content-Addressable Memories	Nov 13, 2020	Few-Shot LearningGeneral Classification	—Unverified
Instance-based Max-margin for Practical Few-shot Recognition	May 27, 2023	Few-Shot Learning	—Unverified
Instance-Conditioned GAN Data Augmentation for Representation Learning	Mar 16, 2023	Data AugmentationFew-Shot Learning	—Unverified
IntCoOp: Interpretability-Aware Vision-Language Prompt Tuning	Jun 19, 2024	AttributeFew-Shot Learning	—Unverified
Integrating Domain Knowledge into Large Language Models for Enhanced Fashion Recommendations	Jan 3, 2025	Few-Shot LearningLanguage Modeling	—Unverified
Integrating Large Language Models with Internet of Things Applications	Oct 25, 2024	Few-Shot Learning	—Unverified
Intelligent Known and Novel Aircraft Recognition -- A Shift from Classification to Similarity Learning for Combat Identification	Feb 26, 2024	ClassificationFew-Shot Learning	—Unverified
Interpolating Convolutional Neural Networks Using Batch Normalization	Sep 1, 2018	Few-Shot LearningStyle Transfer	—Unverified
Interpretable Concept-based Prototypical Networks for Few-Shot Learning	Feb 27, 2022	Few-Shot LearningMeta-Learning	—Unverified
Interpretable Few-shot Learning with Online Attribute Selection	Nov 16, 2022	AttributeFew-Shot Learning	—Unverified
Interpretable Self-supervised Multi-task Learning for COVID-19 Information Retrieval and Extraction	Jun 15, 2021	ArticlesDecision Making	—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