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 51–75 of 2964 papers

Title	Date	Tasks	Status	Hype
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation	Feb 19, 2024	DenoisingFew-Shot Learning	CodeCode Available	2
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains	Feb 15, 2024	Few-Shot LearningMedical Question Answering	CodeCode Available	2
Large Language Models to Enhance Bayesian Optimization	Feb 6, 2024	Bayesian OptimizationFew-Shot Learning	CodeCode Available	2
EHRAgent: Code Empowers Large Language Models for Few-shot Complex Tabular Reasoning on Electronic Health Records	Jan 13, 2024	Code GenerationFew-Shot Learning	CodeCode Available	2
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies	Oct 16, 2023	Few-Shot LearningTime Series	CodeCode Available	2
nnSAM: Plug-and-play Segment Anything Model Improves nnUNet Performance	Sep 29, 2023	Few-Shot LearningHeart Segmentation	CodeCode Available	2
Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation	Jul 27, 2023	3D geometryFew-Shot Learning	CodeCode Available	2
DialogStudio: Towards Richest and Most Diverse Unified Dataset Collection for Conversational AI	Jul 19, 2023	Conversational RecommendationDiversity	CodeCode Available	2
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning	Jun 13, 2023	AllDomain Generalization	CodeCode Available	2
Improving Factuality and Reasoning in Language Models through Multiagent Debate	May 23, 2023	Few-Shot LearningLanguage Modeling	CodeCode Available	2
The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-Tuning	May 23, 2023	Common Sense ReasoningCommon Sense Reasoning (Zero-Shot)	CodeCode Available	2
PointGPT: Auto-regressively Generative Pre-training from Point Clouds	May 19, 2023	3D Point Cloud ClassificationDecoder	CodeCode Available	2
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text	Apr 14, 2023	Few-Shot Learning	CodeCode Available	2
Universal Few-shot Learning of Dense Prediction Tasks with Visual Token Matching	Mar 27, 2023	DecoderFew-Shot Learning	CodeCode Available	2
ReVersion: Diffusion-Based Relation Inversion from Images	Mar 23, 2023	Contrastive LearningFew-Shot Learning	CodeCode Available	2
Prompt, Generate, then Cache: Cascade of Foundation Models makes Strong Few-shot Learners	Mar 3, 2023	Few-Shot LearningRepresentation Learning	CodeCode Available	2
One Fits All:Power General Time Series Analysis by Pretrained LM	Feb 23, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	2
An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation	Feb 13, 2023	Few-Shot LearningLanguage Modelling	CodeCode Available	2
Multimodality Helps Unimodality: Cross-Modal Few-Shot Learning with Multimodal Models	Jan 16, 2023	Audio ClassificationFew-Shot Learning	CodeCode Available	2
Hungry Hungry Hippos: Towards Language Modeling with State Space Models	Dec 28, 2022	8kCoreference Resolution	CodeCode Available	2
Continual Training of Language Models for Few-Shot Learning	Oct 11, 2022	Continual LearningContinual Pretraining	CodeCode Available	2
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model	Aug 8, 2022	Aerial Scene ClassificationFew-Shot Learning	CodeCode Available	2
Atlas: Few-shot Learning with Retrieval Augmented Language Models	Aug 5, 2022	Fact CheckingFew-Shot Learning	CodeCode Available	2
AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model	Aug 2, 2022	Causal Language ModelingCommon Sense Reasoning	CodeCode Available	2
Language Model Cascades	Jul 21, 2022	Few-Shot LearningLanguage Modeling	CodeCode Available	2

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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