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 351–375 of 2964 papers

Title	Date	Tasks	Status	Hype
Discriminative Nearest Neighbor Few-Shot Intent Detection by Transferring Natural Language Inference	Oct 25, 2020	Few-Shot LearningGoal-Oriented Dialog	CodeCode Available	1
Bi-directional Feature Reconstruction Network for Fine-Grained Few-Shot Image Classification	Nov 30, 2022	Few-Shot Image ClassificationFew-Shot Learning	CodeCode Available	1
DETReg: Unsupervised Pretraining with Region Priors for Object Detection	Jun 8, 2021	Few-Shot LearningFew-Shot Object Detection	CodeCode Available	1
Few-Shot Unsupervised Continual Learning through Meta-Examples	Sep 17, 2020	ClusteringContinual Learning	CodeCode Available	1
Detecting Hate Speech with GPT-3	Mar 23, 2021	Few-Shot LearningHate Speech Detection	CodeCode Available	1
Few-Shot Classification with Feature Map Reconstruction Networks	Dec 2, 2020	ClassificationCross-Domain Few-Shot	CodeCode Available	1
FiT: Parameter Efficient Few-shot Transfer Learning for Personalized and Federated Image Classification	Jun 17, 2022	Federated LearningFew-Shot Learning	CodeCode Available	1
Binocular Mutual Learning for Improving Few-shot Classification	Aug 27, 2021	ClassificationDecision Making	CodeCode Available	1
FLEX: Unifying Evaluation for Few-Shot NLP	Jul 15, 2021	Few-Shot LearningLanguage Modeling	CodeCode Available	1
BioBERT: a pre-trained biomedical language representation model for biomedical text mining	Jan 25, 2019	Drug–drug Interaction ExtractionFew-Shot Learning	CodeCode Available	1
FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole Slide Image Classification	Nov 22, 2024	DiagnosticFew-Shot Learning	CodeCode Available	1
Diagnosing Infeasible Optimization Problems Using Large Language Models	Aug 23, 2023	ChatbotDecision Making	CodeCode Available	1
From LSAT: The Progress and Challenges of Complex Reasoning	Aug 2, 2021	Few-Shot LearningLogical Reasoning	CodeCode Available	1
Bitwidth-Adaptive Quantization-Aware Neural Network Training: A Meta-Learning Approach	Jul 20, 2022	Few-Shot LearningMeta-Learning	CodeCode Available	1
FSCE: Few-Shot Object Detection via Contrastive Proposal Encoding	Mar 10, 2021	Contrastive LearningCross-Domain Few-Shot Object Detection	CodeCode Available	1
Fuzzy Graph Neural Network for Few-Shot Learning	Jul 19, 2020	Few-Shot LearningGraph Neural Network	CodeCode Available	1
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions	May 27, 2022	BenchmarkingFew-Shot Image Classification	CodeCode Available	1
Bongard-OpenWorld: Few-Shot Reasoning for Free-form Visual Concepts in the Real World	Oct 16, 2023	Few-Shot LearningForm	CodeCode Available	1
Boosting Few-Shot Classification with View-Learnable Contrastive Learning	Jul 20, 2021	ClassificationContrastive Learning	CodeCode Available	1
Boosting Few-shot Fine-grained Recognition with Background Suppression and Foreground Alignment	Oct 4, 2022	Few-Shot Learning	CodeCode Available	1
Generating Representative Samples for Few-Shot Classification	May 5, 2022	Few-Shot LearningGeneral Classification	CodeCode Available	1
Generating Training Data with Language Models: Towards Zero-Shot Language Understanding	Feb 9, 2022	Few-Shot LearningMNLI-m	CodeCode Available	1
An Embarrassingly Simple Approach to Semi-Supervised Few-Shot Learning	Sep 28, 2022	Few-Shot Learning	CodeCode Available	1
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts	May 24, 2022	Few-Shot LearningLanguage Modelling	CodeCode Available	1
DETA: Denoised Task Adaptation for Few-Shot Learning	Mar 11, 2023	DenoisingFew-Shot Learning	CodeCode Available	1

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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