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 2451–2475 of 2964 papers

Title	Date	Tasks	Status
GPTree: Towards Explainable Decision-Making via LLM-powered Decision Trees	Nov 13, 2024	Decision MakingFeature Engineering	—Unverified
Gradient-Based Meta-Learning Using Uncertainty to Weigh Loss for Few-Shot Learning	Aug 17, 2022	Few-Shot LearningMeta-Learning	—Unverified
Gradient Boosting Trees and Large Language Models for Tabular Data Few-Shot Learning	Nov 6, 2024	DiversityFew-Shot Learning	—Unverified
Gradient-Regulated Meta-Prompt Learning for Generalizable Vision-Language Models	Mar 12, 2023	Domain GeneralizationFew-Shot Learning	—Unverified
Gradual Relation Network: Decoding Intuitive Upper Extremity Movement Imaginations Based on Few-Shot EEG Learning	May 6, 2020	Brain Computer InterfaceEEG	—Unverified
Grammatical information in BERT sentence embeddings as two-dimensional arrays	Dec 15, 2023	Few-Shot LearningSentence	—Unverified
Graph-DPEP: Decomposed Plug and Ensemble Play for Few-Shot Document Relation Extraction with Graph-of-Thoughts Reasoning	Nov 5, 2024	Document-level Relation ExtractionFew-Shot Learning	—Unverified
Graph Machine Learning in the Era of Large Language Models (LLMs)	Apr 23, 2024	Few-Shot LearningKnowledge Graphs	—Unverified
Graph Mining under Data scarcity	Jun 7, 2024	ClassificationFew-Shot Learning	—Unverified
Graph Transformer	May 1, 2019	Few-Shot LearningGeneral Classification	—Unverified
Growing from Exploration: A self-exploring framework for robots based on foundation models	Jan 24, 2024	Few-Shot Learning	—Unverified
GS-PT: Exploiting 3D Gaussian Splatting for Comprehensive Point Cloud Understanding via Self-supervised Learning	Sep 8, 2024	3DGS3D Object Classification	—Unverified
Guided Deep Metric Learning	Jun 4, 2022	Few-Shot LearningKnowledge Distillation	—Unverified
HAVE-Net: Hallucinated Audio-Visual Embeddings for Few-Shot Classification with Unimodal Cues	Sep 23, 2023	Few-Shot Learning	—Unverified
HazardNet: Road Debris Detection by Augmentation of Synthetic Models	Mar 14, 2023	Few-Shot Learning	—Unverified
HCL-TAT: A Hybrid Contrastive Learning Method for Few-shot Event Detection with Task-Adaptive Threshold	Oct 17, 2022	Contrastive LearningEvent Detection	—Unverified
Head2HeadFS: Video-based Head Reenactment with Few-shot Learning	Mar 30, 2021	Few-Shot LearningPose Transfer	—Unverified
HetMAML: Task-Heterogeneous Model-Agnostic Meta-Learning for Few-Shot Learning Across Modalities	May 17, 2021	Few-Shot LearningMeta-Learning	—Unverified
HFBRI-MAE: Handcrafted Feature Based Rotation-Invariant Masked Autoencoder for 3D Point Cloud Analysis	Apr 19, 2025	Few-Shot LearningSelf-Supervised Learning	—Unverified
Hierarchical Cross Contrastive Learning of Visual Representations	Sep 29, 2021	Contrastive LearningFew-Shot Learning	—Unverified
Hierarchical end-to-end autonomous navigation through few-shot waypoint detection	Sep 23, 2024	Autonomous NavigationFew-Shot Learning	—Unverified
Hierarchical Knowledge Distillation on Text Graph for Data-limited Attribute Inference	Jan 10, 2024	AttributeFew-Shot Learning	—Unverified
Hierarchical Local-Global Feature Learning for Few-shot Malicious Traffic Detection	Apr 1, 2025	Few-Shot LearningTraffic Classification	—Unverified
Hierarchical Material Recognition from Local Appearance	May 28, 2025	Few-Shot LearningGraph Attention	—Unverified
Hierarchical Meta Learning	Apr 19, 2019	Few-Shot LearningMeta-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