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	Score
Overcoming challenges in leveraging GANs for few-shot data augmentation	Mar 30, 2022	ClassificationData Augmentation	CodeCode Available	1	5
FewCLUE: A Chinese Few-shot Learning Evaluation Benchmark	Jul 15, 2021	Few-Shot LearningMachine Reading Comprehension	CodeCode Available	1	5
3D-IDS: Doubly Disentangled Dynamic Intrusion Detection	Jul 2, 2023	DisentanglementFew-Shot Learning	CodeCode Available	1	5
CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors	May 9, 2023	Code GenerationFew-Shot Learning	CodeCode Available	1	5
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	5
Chameleon: A MatMul-Free Temporal Convolutional Network Accelerator for End-to-End Few-Shot and Continual Learning from Sequential Data	May 30, 2025	Continual LearningFew-Shot Learning	CodeCode Available	1	5
Few-Shot Bot: Prompt-Based Learning for Dialogue Systems	Oct 15, 2021	ChatbotDialogue State Tracking	CodeCode Available	1	5
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search	Nov 3, 2020	Domain AdaptationFew-Shot Learning	CodeCode Available	1	5
Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration	Dec 8, 2023	class-incremental learningClass Incremental Learning	CodeCode Available	1	5
Few-Shot Diffusion Models	May 30, 2022	DenoisingFew-Shot Learning	CodeCode Available	1	5
Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models	Sep 20, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	1	5
Code Summarization Beyond Function Level	Feb 23, 2025	Code SummarizationFew-Shot Learning	CodeCode Available	1	5
Few-Shot Learning by Integrating Spatial and Frequency Representation	May 11, 2021	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa	Jan 24, 2023	Few-Shot LearningPlant Phenotyping	CodeCode Available	1	5
Few Shot Learning Framework to Reduce Inter-observer Variability in Medical Images	Aug 7, 2020	Few-Shot Learning	CodeCode Available	1	5
A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt Learning	Feb 2, 2024	Few-Shot LearningGraph Representation Learning	CodeCode Available	1	5
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning	Mar 17, 2022	AttributeFew-Shot Image Classification	CodeCode Available	1	5
Few-Shot Learning with a Strong Teacher	Jul 1, 2021	Few-Shot LearningMeta-Learning	CodeCode Available	1	5
Adaptive Subspaces for Few-Shot Learning	Jun 1, 2020	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
RARR: Researching and Revising What Language Models Say, Using Language Models	Oct 17, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	1	5
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	5
CoNeRF: Controllable Neural Radiance Fields	Dec 3, 2021	3D Face Modelling3D Reconstruction	CodeCode Available	1	5
FAPIS: A Few-shot Anchor-free Part-based Instance Segmenter	Mar 31, 2021	Few-shot Instance SegmentationFew-Shot Learning	CodeCode Available	1	5
BankNote-Net: Open dataset for assistive universal currency recognition	Apr 7, 2022	Contrastive LearningFew-Shot Learning	CodeCode Available	1	5
Feature Generation for Long-tail Classification	Nov 10, 2021	ClassificationFew-Shot Learning	CodeCode Available	1	5

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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