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 251–275 of 2964 papers

Title	Date	Tasks	Status	Hype	Score
Deep Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study	Mar 6, 2020	Few-Shot LearningModel Selection	CodeCode Available	1	5
Charting the Right Manifold: Manifold Mixup for Few-shot Learning	Jul 28, 2019	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels	Oct 11, 2019	Bayesian InferenceDomain Adaptation	CodeCode Available	1	5
DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning	Mar 15, 2020	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
Enhancing Activity Prediction Models in Drug Discovery with the Ability to Understand Human Language	Mar 6, 2023	Activity PredictionAttribute	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
Overcoming challenges in leveraging GANs for few-shot data augmentation	Mar 30, 2022	ClassificationData Augmentation	CodeCode Available	1	5
Channel Importance Matters in Few-Shot Image Classification	Jun 16, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
Enhancing Few-shot Image Classification with Cosine Transformer	Nov 13, 2022	ClassificationFew-Shot Image Classification	CodeCode Available	1	5
Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models	Apr 9, 2024	Few-Shot LearningLanguage Modelling	CodeCode Available	1	5
Emoji Attack: A Method for Misleading Judge LLMs in Safety Risk Detection	Nov 1, 2024	Few-Shot Learning	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
Adaptive Subspaces for Few-Shot Learning	Jun 1, 2020	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1	5
CLARA: Multilingual Contrastive Learning for Audio Representation Acquisition	Oct 18, 2023	Audio ClassificationContrastive Learning	CodeCode Available	1	5
Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs	Oct 15, 2023	Few-Shot LearningGraph Learning	CodeCode Available	1	5
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	5
Expanding Event Modality Applications through a Robust CLIP-Based Encoder	Dec 4, 2024	Few-Shot LearningObject Recognition	CodeCode Available	1	5
Few-Shot Bot: Prompt-Based Learning for Dialogue Systems	Oct 15, 2021	ChatbotDialogue State Tracking	CodeCode Available	1	5
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	5
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIs	Dec 27, 2024	EEGFew-Shot Learning	CodeCode Available	1	5
Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes	Oct 8, 2024	ArticlesClassification	CodeCode Available	1	5
Calibrate Before Use: Improving Few-Shot Performance of Language Models	Feb 19, 2021	Few-Shot Learning	CodeCode Available	1	5
CaesarNeRF: Calibrated Semantic Representation for Few-shot Generalizable Neural Rendering	Nov 27, 2023	Few-Shot LearningNeRF	CodeCode Available	1	5
Can Explanations Be Useful for Calibrating Black Box Models?	Oct 14, 2021	Extractive Question-AnsweringFew-Shot Learning	CodeCode Available	1	5
BSNet: Bi-Similarity Network for Few-shot Fine-grained Image Classification	Nov 29, 2020	Few-Shot LearningFine-Grained Image Classification	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