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 1626–1650 of 2964 papers

Title	Date	Tasks	Status	Hype
Building a Role Specified Open-Domain Dialogue System Leveraging Large-Scale Language Models	Apr 30, 2022	Few-Shot Learning	CodeCode Available	1
Look Closer to Supervise Better: One-Shot Font Generation via Component-Based Discriminator	Apr 30, 2022	Few-Shot LearningFont Generation	CodeCode Available	1
EasyNLP: A Comprehensive and Easy-to-use Toolkit for Natural Language Processing	Apr 30, 2022	Few-Shot LearningKnowledge Distillation	—Unverified	0
Flamingo: a Visual Language Model for Few-Shot Learning	Apr 29, 2022	Few-Shot LearningGenerative Visual Question Answering	CodeCode Available	4
On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model	Apr 28, 2022	Few-Shot LearningIn-Context Learning	—Unverified	0
Executive Function: A Contrastive Value Policy for Resampling and Relabeling Perceptions via Hindsight Summarization?	Apr 27, 2022	Continual LearningFew-Shot Learning	—Unverified	0
Function-words Enhanced Attention Networks for Few-Shot Inverse Relation Classification	Apr 26, 2022	Few-Shot LearningMeta-Learning	—Unverified	0
Meta-free few-shot learning via representation learning with weight averaging	Apr 26, 2022	ClassificationFew-Shot Learning	—Unverified	0
Super-Prompting: Utilizing Model-Independent Contextual Data to Reduce Data Annotation Required in Visual Commonsense Tasks	Apr 25, 2022	Few-Shot LearningIn-Context Learning	—Unverified	0
Few-Shot Speaker Identification Using Depthwise Separable Convolutional Network with Channel Attention	Apr 24, 2022	Audio ClassificationFew-Shot Learning	—Unverified	0
Realistic Evaluation of Transductive Few-Shot Learning	Apr 24, 2022	Few-Shot Learning	CodeCode Available	1
Data Distributional Properties Drive Emergent In-Context Learning in Transformers	Apr 22, 2022	Few-Shot LearningIn-Context Learning	CodeCode Available	1
Few-Shot Object Detection with Proposal Balance Refinement	Apr 22, 2022	Few-Shot LearningFew-Shot Object Detection	—Unverified	0
Zero and Few-shot Learning for Author Profiling	Apr 22, 2022	Author ProfilingFew-Shot Learning	—Unverified	0
Few-shot learning for medical text: A systematic review	Apr 21, 2022	ArticlesFew-Shot Learning	—Unverified	0
Active Few-Shot Learning with FASL	Apr 20, 2022	Active LearningFew-Shot Learning	CodeCode Available	0
Less than Few: Self-Shot Video Instance Segmentation	Apr 19, 2022	Few-Shot LearningInstance Segmentation	—Unverified	0
A Study on Prompt-based Few-Shot Learning Methods for Belief State Tracking in Task-oriented Dialog Systems	Apr 18, 2022	Few-Shot LearningLanguage Modelling	—Unverified	0
Learning Compositional Representations for Effective Low-Shot Generalization	Apr 17, 2022	AttributeDomain Adaptation	—Unverified	0
Few-Shot Transfer Learning to improve Chest X-Ray pathology detection using limited triplets	Apr 16, 2022	DiagnosticFew-Shot Learning	CodeCode Available	0
Multi-Modal Few-Shot Object Detection with Meta-Learning-Based Cross-Modal Prompting	Apr 16, 2022	Few-Shot LearningFew-Shot Object Detection	—Unverified	0
mGPT: Few-Shot Learners Go Multilingual	Apr 15, 2022	Cross-Lingual Natural Language InferenceCross-Lingual Paraphrase Identification	CodeCode Available	2
In-BoXBART: Get Instructions into Biomedical Multi-Task Learning	Apr 15, 2022	Few-Shot LearningMulti-Task Learning	CodeCode Available	2
Pushing the Limits of Simple Pipelines for Few-Shot Learning: External Data and Fine-Tuning Make a Difference	Apr 15, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
Impossible Triangle: What's Next for Pre-trained Language Models?	Apr 13, 2022	Data AugmentationFew-Shot 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