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 201–225 of 2964 papers

Title	Date	Tasks	Status	Hype
LLM4SGG: Large Language Models for Weakly Supervised Scene Graph Generation	Oct 16, 2023	Few-Shot LearningLarge Language Model	CodeCode Available	1
In-Context Learning with Iterative Demonstration Selection	Oct 15, 2023	Few-Shot LearningIn-Context Learning	CodeCode Available	1
Leveraging Large Language Models for Node Generation in Few-Shot Learning on Text-Attributed Graphs	Oct 15, 2023	Few-Shot LearningGraph Learning	CodeCode Available	1
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining	Oct 11, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	1
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training	Oct 3, 2023	Contrastive LearningEquation Discovery	CodeCode Available	1
Recurrent Hypernetworks are Surprisingly Strong in Meta-RL	Sep 26, 2023	Deep Reinforcement LearningFew-Shot Learning	CodeCode Available	1
Domain Adaptive Few-Shot Open-Set Learning	Sep 22, 2023	cross-domain few-shot learningFew-Shot Learning	CodeCode Available	1
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input Representation	Sep 18, 2023	Contrastive LearningData Augmentation	CodeCode Available	1
SCT: A Simple Baseline for Parameter-Efficient Fine-Tuning via Salient Channels	Sep 15, 2023	Domain GeneralizationFew-Shot Learning	CodeCode Available	1
GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection	Sep 12, 2023	Anomaly DetectionFew-Shot Learning	CodeCode Available	1
Self-Correlation and Cross-Correlation Learning for Few-Shot Remote Sensing Image Semantic Segmentation	Sep 11, 2023	Few-Shot LearningSegmentation	CodeCode Available	1
DePT: Decomposed Prompt Tuning for Parameter-Efficient Fine-tuning	Sep 11, 2023	Few-Shot Learningparameter-efficient fine-tuning	CodeCode Available	1
Few-Shot Medical Image Segmentation via a Region-enhanced Prototypical Transformer	Sep 9, 2023	DiversityFew-Shot Learning	CodeCode Available	1
CDFSL-V: Cross-Domain Few-Shot Learning for Videos	Sep 7, 2023	Action RecognitionCross-Domain Few-Shot	CodeCode Available	1
Pretraining Representations for Bioacoustic Few-shot Detection using Supervised Contrastive Learning	Sep 2, 2023	Contrastive LearningData Augmentation	CodeCode Available	1
Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning	Aug 31, 2023	DecoderFew-Shot Learning	CodeCode Available	1
Read-only Prompt Optimization for Vision-Language Few-shot Learning	Aug 29, 2023	Domain GeneralizationFew-Shot Learning	CodeCode Available	1
AskIt: Unified Programming Interface for Programming with Large Language Models	Aug 29, 2023	Code GenerationFew-Shot Learning	CodeCode Available	1
Transfer Learning for Microstructure Segmentation with CS-UNet: A Hybrid Algorithm with Transformer and CNN Encoders	Aug 26, 2023	Few-Shot LearningImage Segmentation	CodeCode Available	1
Diagnosing Infeasible Optimization Problems Using Large Language Models	Aug 23, 2023	ChatbotDecision Making	CodeCode Available	1
Link-Context Learning for Multimodal LLMs	Aug 15, 2023	Few-Shot LearningIn-Context Learning	CodeCode Available	1
Dialogue for Prompting: a Policy-Gradient-Based Discrete Prompt Generation for Few-shot Learning	Aug 14, 2023	Few-Shot LearningReinforcement Learning (RL)	CodeCode Available	1
LLMeBench: A Flexible Framework for Accelerating LLMs Benchmarking	Aug 9, 2023	BenchmarkingFew-Shot Learning	CodeCode Available	1
Learning Multi-modal Representations by Watching Hundreds of Surgical Video Lectures	Jul 27, 2023	Automatic Speech RecognitionContrastive Learning	CodeCode Available	1
Self-supervised Few-shot Learning for Semantic Segmentation: An Annotation-free Approach	Jul 26, 2023	Few-Shot LearningFew-Shot Semantic Segmentation	CodeCode Available	1

Show:10 25 50

← PrevPage 9 of 119Next →

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