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 1651–1675 of 2964 papers

Title	Date	Tasks	Status
What Makes Data-to-Text Generation Hard for Pretrained Language Models?	May 23, 2022	Data-to-Text GenerationFew-Shot Learning	—Unverified
What Makes Good Few-shot Examples for Vision-Language Models?	May 22, 2024	Active LearningFew-Shot Learning	—Unverified
What's in a Measurement? Using GPT-3 on SemEval 2021 Task 8 -- MeasEval	Jun 28, 2021	Few-Shot LearningLanguage Modelling	—Unverified
When Facial Expression Recognition Meets Few-Shot Learning: A Joint and Alternate Learning Framework	Jan 18, 2022	Cross-Domain Few-Shotcross-domain few-shot learning	—Unverified
When hard negative sampling meets supervised contrastive learning	Aug 28, 2023	Contrastive LearningFew-Shot Learning	—Unverified
When the Few Outweigh the Many: Illicit Content Recognition with Few-Shot Learning	Nov 28, 2023	Few-Shot Learning	—Unverified
Where2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objects	Sep 14, 2023	Efficient ExplorationFew-Shot Learning	—Unverified
Which images to label for few-shot medical landmark detection?	Dec 7, 2021	Few-Shot Learning	—Unverified
Will Multi-modal Data Improves Few-shot Learning?	Jul 25, 2021	Few-Shot Learning	—Unverified
WisPerMed at BioLaySumm: Adapting Autoregressive Large Language Models for Lay Summarization of Scientific Articles	May 20, 2024	ArticlesFew-Shot Learning	—Unverified
WisPerMed at "Discharge Me!": Advancing Text Generation in Healthcare with Large Language Models, Dynamic Expert Selection, and Priming Techniques on MIMIC-IV	May 18, 2024	Few-Shot LearningText Generation	—Unverified
Wordcraft: a Human-AI Collaborative Editor for Story Writing	Jul 15, 2021	Few-Shot Learning	—Unverified
xCoT: Cross-lingual Instruction Tuning for Cross-lingual Chain-of-Thought Reasoning	Jan 13, 2024	Few-Shot LearningLanguage Modelling	—Unverified
Zero and Few-shot Learning for Author Profiling	Apr 22, 2022	Author ProfilingFew-Shot Learning	—Unverified
Zero and Few Shot Learning with Semantic Feature Synthesis and Competitive Learning	Oct 19, 2018	AttributeFew-Shot Learning	—Unverified
Zero- and Few-Shot NLP with Pretrained Language Models	May 1, 2022	Few-Shot Learning	—Unverified
Zero-Shot and Few-Shot Learning for Lung Cancer Multi-Label Classification using Vision Transformer	May 30, 2022	Few-Shot LearningLung Cancer Diagnosis	—Unverified
Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking	Jan 18, 2025	Binary ClassificationFact Checking	—Unverified
Zero-Shot Cross-Lingual Document-Level Event Causality Identification with Heterogeneous Graph Contrastive Transfer Learning	Mar 5, 2024	Event Causality IdentificationFew-Shot Learning	—Unverified
Zero-Shot Learning and its Applications from Autonomous Vehicles to COVID-19 Diagnosis: A Review	Apr 29, 2020	Autonomous VehiclesCOVID-19 Diagnosis	—Unverified
Zero-Shot Learning via Class-Conditioned Deep Generative Models	Nov 15, 2017	Few-Shot LearningZero-Shot Learning	—Unverified
Z-Score Normalization, Hubness, and Few-Shot Learning	Jan 1, 2021	Few-Shot LearningMeta-Learning	—Unverified
Incremental Few-Shot Learning for Pedestrian Attribute Recognition	Jun 2, 2019	AttributeFew-Shot Learning	—Unverified
Teaching Pretrained Models with Commonsense Reasoning: A Preliminary KB-Based Approach	Sep 20, 2019	Few-Shot LearningLogical Reasoning	—Unverified
A Rational Model of Dimension-reduced Human Categorization	May 22, 2023	Few-Shot Learningmodel	—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