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 301–325 of 2964 papers

Title	Date	Tasks	Status	Hype
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis	Jul 10, 2024	Data AugmentationFew-Shot Learning	CodeCode Available	1
Diversified in-domain synthesis with efficient fine-tuning for few-shot classification	Dec 5, 2023	DiversityFew-Shot Image Classification	CodeCode Available	1
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning	Mar 17, 2022	AttributeFew-Shot Image Classification	CodeCode Available	1
Bias-Eliminated Semantic Refinement for Any-Shot Learning	Feb 10, 2022	Few-Shot LearningGeneralized Zero-Shot Learning	CodeCode Available	1
All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining	Feb 15, 2024	AllFew-Shot Learning	CodeCode Available	1
Dual Adaptive Representation Alignment for Cross-domain Few-shot Learning	Jun 18, 2023	Cross-Domain Few-Shotcross-domain few-shot learning	CodeCode Available	1
RARR: Researching and Revising What Language Models Say, Using Language Models	Oct 17, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	1
Easter2.0: Improving convolutional models for handwritten text recognition	May 30, 2022	Data AugmentationFew-Shot Learning	CodeCode Available	1
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIs	Dec 27, 2024	EEGFew-Shot Learning	CodeCode Available	1
Effect of Pre-Training Scale on Intra- and Inter-Domain Full and Few-Shot Transfer Learning for Natural and Medical X-Ray Chest Images	May 31, 2021	Few-Shot LearningImage Classification	CodeCode Available	1
Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models	Sep 20, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	1
DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot Learning	Jan 1, 2024	DenoisingFew-Shot Learning	CodeCode Available	1
Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models	Apr 9, 2024	Few-Shot LearningLanguage Modelling	CodeCode Available	1
Emoji Attack: A Method for Misleading Judge LLMs in Safety Risk Detection	Nov 1, 2024	Few-Shot Learning	CodeCode Available	1
Enhancing Few-shot Image Classification with Cosine Transformer	Nov 13, 2022	ClassificationFew-Shot Image Classification	CodeCode Available	1
Enhancing Information Maximization with Distance-Aware Contrastive Learning for Source-Free Cross-Domain Few-Shot Learning	Mar 4, 2024	Contrastive LearningCross-Domain Few-Shot	CodeCode Available	1
ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot Learning	Apr 26, 2023	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Evaluating Weakly Supervised Object Localization Methods Right	Jan 21, 2020	Few-Shot LearningModel Selection	CodeCode Available	1
Diagnosing Infeasible Optimization Problems Using Large Language Models	Aug 23, 2023	ChatbotDecision Making	CodeCode Available	1
Domain Generalizer: A Few-shot Meta Learning Framework for Domain Generalization in Medical Imaging	Aug 18, 2020	Computed Tomography (CT)Domain Generalization	CodeCode Available	1
A Comprehensive Evaluation of Multi-task Learning and Multi-task Pre-training on EHR Time-series Data	Jul 20, 2020	Few-Shot LearningMulti-Task Learning	CodeCode Available	1
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning	Mar 1, 2021	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Expanding Event Modality Applications through a Robust CLIP-Based Encoder	Dec 4, 2024	Few-Shot LearningObject Recognition	CodeCode Available	1
BankNote-Net: Open dataset for assistive universal currency recognition	Apr 7, 2022	Contrastive LearningFew-Shot Learning	CodeCode Available	1
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning	Mar 15, 2020	ClassificationFew-Shot Image Classification	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