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 701–725 of 2964 papers

Title	Date	Tasks	Status	Hype
How Important is Domain Specificity in Language Models and Instruction Finetuning for Biomedical Relation Extraction?	Feb 21, 2024	Few-Shot LearningRelation	—Unverified	0
VL-Trojan: Multimodal Instruction Backdoor Attacks against Autoregressive Visual Language Models	Feb 21, 2024	Backdoor AttackFew-Shot Learning	—Unverified	0
OPDAI at SemEval-2024 Task 6: Small LLMs can Accelerate Hallucination Detection with Weakly Supervised Data	Feb 20, 2024	Few-Shot LearningHallucination	—Unverified	0
Few-shot clinical entity recognition in English, French and Spanish: masked language models outperform generative model prompting	Feb 20, 2024	Few-Shot Learningnamed-entity-recognition	—Unverified	0
Me LLaMA: Foundation Large Language Models for Medical Applications	Feb 20, 2024	Few-Shot LearningGPU	CodeCode Available	2
DeepCode AI Fix: Fixing Security Vulnerabilities with Large Language Models	Feb 19, 2024	Code RepairFew-Shot Learning	—Unverified	0
Spatio-Temporal Few-Shot Learning via Diffusive Neural Network Generation	Feb 19, 2024	DenoisingFew-Shot Learning	CodeCode Available	2
In-Context Learning Demonstration Selection via Influence Analysis	Feb 19, 2024	Few-Shot LearningIn-Context Learning	CodeCode Available	1
Modularized Networks for Few-shot Hateful Meme Detection	Feb 19, 2024	Few-Shot LearningIn-Context Learning	CodeCode Available	0
Grasping the Essentials: Tailoring Large Language Models for Zero-Shot Relation Extraction	Feb 17, 2024	Few-Shot LearningLanguage Modelling	CodeCode Available	0
Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models	Feb 15, 2024	FairnessFew-Shot Learning	—Unverified	0
BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains	Feb 15, 2024	Few-Shot LearningMedical Question Answering	CodeCode Available	2
Self-Augmented In-Context Learning for Unsupervised Word Translation	Feb 15, 2024	Bilingual Lexicon InductionCross-Lingual Word Embeddings	CodeCode Available	0
All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining	Feb 15, 2024	AllFew-Shot Learning	CodeCode Available	1
How Secure Are Large Language Models (LLMs) for Navigation in Urban Environments?	Feb 14, 2024	Autonomous DrivingFew-Shot Learning	—Unverified	0
Few-Shot Learning with Uncertainty-based Quadruplet Selection for Interference Classification in GNSS Data	Feb 9, 2024	Few-Shot Learning	—Unverified	0
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning	Feb 9, 2024	Contrastive LearningDisentanglement	—Unverified	0
Advancing Video Anomaly Detection: A Concise Review and a New Dataset	Feb 7, 2024	Anomaly DetectionDiversity	—Unverified	0
L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models	Feb 7, 2024	Few-Shot LearningIn-Context Learning	—Unverified	0
Rethinking Skill Extraction in the Job Market Domain using Large Language Models	Feb 6, 2024	Few-Shot LearningIn-Context Learning	CodeCode Available	0
Exploring Low-Resource Medical Image Classification with Weakly Supervised Prompt Learning	Feb 6, 2024	Few-Shot Learningimage-classification	—Unverified	0
Large Language Models to Enhance Bayesian Optimization	Feb 6, 2024	Bayesian OptimizationFew-Shot Learning	CodeCode Available	2
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models	Feb 6, 2024	Few-Shot LearningKnowledge Distillation	CodeCode Available	1
A Complete Survey on Contemporary Methods, Emerging Paradigms and Hybrid Approaches for Few-Shot Learning	Feb 5, 2024	Few-Shot LearningIn-Context Learning	—Unverified	0
Automatic Combination of Sample Selection Strategies for Few-Shot Learning	Feb 5, 2024	Few-Shot LearningIn-Context Learning	—Unverified	0

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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