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 151–175 of 2964 papers

Title	Date	Tasks	Status
Is LLM an Overconfident Judge? Unveiling the Capabilities of LLMs in Detecting Offensive Language with Annotation Disagreement	Feb 10, 2025	Binary ClassificationDecision Making	CodeCode Available
WatchGuardian: Enabling User-Defined Personalized Just-in-Time Intervention on Smartwatch	Feb 9, 2025	Data AugmentationFew-Shot Learning	—Unverified
Transforming Multimodal Models into Action Models for Radiotherapy	Feb 6, 2025	AnatomyFew-Shot Learning	—Unverified
OmniRL: In-Context Reinforcement Learning by Large-Scale Meta-Training in Randomized Worlds	Feb 5, 2025	Few-Shot LearningImitation Learning	—Unverified
RoboGrasp: A Universal Grasping Policy for Robust Robotic Control	Feb 5, 2025	Few-Shot LearningImitation Learning	—Unverified
An Analysis of LLM Fine-Tuning and Few-Shot Learning for Flaky Test Detection and Classification	Feb 4, 2025	Few-Shot Learning	—Unverified
FewTopNER: Integrating Few-Shot Learning with Topic Modeling and Named Entity Recognition in a Multilingual Framework	Feb 4, 2025	Entity DisambiguationFew-Shot Learning	CodeCode Available
Can LLMs Assist Annotators in Identifying Morality Frames? -- Case Study on Vaccination Debate on Social Media	Feb 4, 2025	Few-Shot Learning	—Unverified
Learning to Learn Weight Generation via Local Consistency Diffusion	Feb 3, 2025	Domain GeneralizationFew-Shot Learning	—Unverified
Memory-Efficient Fine-Tuning of Transformers via Token Selection	Jan 31, 2025	Few-Shot LearningQuestion Answering	CodeCode Available
Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs	Jan 31, 2025	Few-Shot LearningIn-Context Learning	—Unverified
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks	Jan 30, 2025	Brain Computer InterfaceClassification	—Unverified
Unraveling the Capabilities of Language Models in News Summarization	Jan 30, 2025	BenchmarkingFew-Shot Learning	CodeCode Available
One Head Eight Arms: Block Matrix based Low Rank Adaptation for CLIP-based Few-Shot Learning	Jan 28, 2025	Few-Shot LearningGPU	—Unverified
Distilling Large Language Models for Network Active Queue Management	Jan 28, 2025	Few-Shot LearningManagement	—Unverified
Few Edges Are Enough: Few-Shot Network Attack Detection with Graph Neural Networks	Jan 28, 2025	Few-Shot LearningSelf-Supervised Learning	—Unverified
AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies	Jan 28, 2025	Few-Shot LearningFew-Shot Semantic Segmentation	—Unverified
Closed-Form Feedback-Free Learning with Forward Projection	Jan 27, 2025	Few-Shot LearningForm	CodeCode Available
SampleLLM: Optimizing Tabular Data Synthesis in Recommendations	Jan 27, 2025	Few-Shot LearningRecommendation Systems	—Unverified
Evaluating Data Influence in Meta Learning	Jan 27, 2025	Bilevel OptimizationComputational Efficiency	—Unverified
Complementary Subspace Low-Rank Adaptation of Vision-Language Models for Few-Shot Classification	Jan 25, 2025	Few-Shot Learningparameter-efficient fine-tuning	—Unverified
A Zero-Shot LLM Framework for Automatic Assignment Grading in Higher Education	Jan 24, 2025	Few-Shot LearningLanguage Modeling	CodeCode Available
CVOCSemRPL: Class-Variance Optimized Clustering, Semantic Information Injection and Restricted Pseudo Labeling based Improved Semi-Supervised Few-Shot Learning	Jan 24, 2025	ClusteringFew-Shot Learning	—Unverified
Geometric Mean Improves Loss For Few-Shot Learning	Jan 24, 2025	Few-Shot Image ClassificationFew-Shot Learning	—Unverified
Evaluating and Improving Graph to Text Generation with Large Language Models	Jan 24, 2025	DiversityFew-Shot Learning	CodeCode Available

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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