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 1501–1525 of 2964 papers

Title	Date	Tasks	Status
TablEye: Seeing small Tables through the Lens of Images	Jul 4, 2023	Few-Shot Learning	—Unverified
Tabular Few-Shot Generalization Across Heterogeneous Feature Spaces	Nov 16, 2023	DecoderFew-Shot Learning	—Unverified
Tackling Non-forgetting and Forward Transfer with a Unified Lifelong Learning Approach	Jun 12, 2020	Few-Shot LearningLifelong learning	—Unverified
TAEN: Temporal Aware Embedding Network for Few-Shot Action Recognition	Apr 21, 2020	3D Face ReconstructionAction Detection	—Unverified
Tailored-LLaMA: Optimizing Few-Shot Learning in Pruned LLaMA Models with Task-Specific Prompts	Oct 24, 2024	Few-Shot LearningSpecificity	—Unverified
Target-Free Compound Activity Prediction via Few-Shot Learning	Nov 27, 2023	Activity PredictionDrug Discovery	—Unverified
Task-Adaptive Clustering for Semi-Supervised Few-Shot Classification	Mar 18, 2020	ClassificationClustering	—Unverified
Task-Adaptive Feature Transformer for Few-Shot Segmentation	Oct 22, 2020	Few-Shot LearningSegmentation	—Unverified
Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation	Feb 14, 2022	Few-Shot LearningSegmentation	—Unverified
Task-Agnostic Meta-Learning for Few-shot Learning	May 20, 2018	ClassificationFew-Shot Learning	—Unverified
Task Agnostic Meta-Learning for Few-Shot Learning	Jun 1, 2019	Few-Shot LearningGeneral Classification	—Unverified
Task Attended Meta-Learning for Few-Shot Learning	Jun 20, 2021	Few-Shot LearningMeta-Learning	—Unverified
Task-aware Adaptive Learning for Cross-domain Few-shot Learning	Jan 1, 2023	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware	Oct 26, 2021	Few-Shot LearningMalware Detection	—Unverified
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems	Oct 7, 2023	Computational EfficiencyFew-Shot Learning	—Unverified
Task-Aware Part Mining Network for Few-Shot Learning	Jan 1, 2021	Few-Shot LearningMeta-Learning	—Unverified
Task-Prior Conditional Variational Auto-Encoder for Few-Shot Image Classification	May 30, 2022	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Task-Specific Preconditioner for Cross-Domain Few-Shot Learning	Dec 20, 2024	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
Task Weighting in Meta-learning with Trajectory Optimisation	Jan 4, 2023	Few-Shot LearningMeta-Learning	—Unverified
TEAM UFAL @ CreativeSumm 2022: BART and SamSum based few-shot approach for creative Summarization	Oct 1, 2022	Few-Shot Learning	—Unverified
Technical Report -- Competition Solution for Prompt Tuning using Pretrained Language Model	Dec 13, 2022	Few-Shot LearningLanguage Modeling	—Unverified
Technical Report on Neural Language Models and Few-Shot Learning for Systematic Requirements Processing in MDSE	Nov 16, 2022	Few-Shot LearningLanguage Modelling	—Unverified
Template-free Prompt Tuning for Few-shot NER	Jan 16, 2022	Few-Shot LearningFew-shot NER	—Unverified
Temporal-Viewpoint Transportation Plan for Skeletal Few-shot Action Recognition	Oct 30, 2022	Action RecognitionDynamic Time Warping	—Unverified
Text2VP: Generative AI for Visual Programming and Parametric Modeling	Jun 9, 2024	Few-Shot 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