SOTAVerified

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

Showing 22012250 of 2964 papers

TitleStatusHype
Image Augmentation for Multitask Few-Shot Learning: Agricultural Domain Use-CaseCode1
Enabling the Network to Surf the Internet0
Dual-Awareness Attention for Few-Shot Object DetectionCode1
Two Sides of Meta-Learning Evaluation: In vs. Out of DistributionCode0
Few-shot Network Anomaly Detection via Cross-network Meta-learningCode1
Few Shot Learning for Information Verification0
MetaDelta: A Meta-Learning System for Few-shot Image ClassificationCode1
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-LearningCode1
Calibrate Before Use: Improving Few-Shot Performance of Language ModelsCode1
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View0
Grid Cell Path Integration For Movement-Based Visual Object RecognitionCode0
Semi Supervised Learning For Few-shot Audio Classification By Episodic Triplet Mining0
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental LearningCode1
One-shot learning for the long term: consolidation with an artificial hippocampal algorithm0
Multi-Objective Meta Learning0
A New Look and Convergence Rate of Federated Multi-Task Learning with Laplacian RegularizationCode1
Large-Scale Meta-Learning with Continual Trajectory Shifting0
Model-Agnostic Graph Regularization for Few-Shot Learning0
COVID-19 detection from scarce chest x-ray image data using few-shot deep learning approachCode1
Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural networkCode1
Partial Is Better Than All: Revisiting Fine-tuning Strategy for Few-shot Learning0
End-to-end Generative Zero-shot Learning via Few-shot LearningCode0
Few-shot time series segmentation using prototype-defined infinite hidden Markov models0
Feature Representation in Deep Metric Embeddings0
Hyperspherical embedding for novel class classification0
Neural Data Augmentation via Example ExtrapolationCode0
Few-shot Learning for CT Scan based COVID-19 Diagnosis0
Few-shot Image Classification with Multi-Facet Prototypes0
Few-Shot Learning for Road Object Detection0
Generalising via Meta-Examples for Continual Learning in the WildCode1
Similarity of Classification TasksCode0
Edge-Labeling based Directed Gated Graph Network for Few-shot LearningCode0
Combat Data Shift in Few-shot Learning with Knowledge Graph0
Supervised Momentum Contrastive Learning for Few-Shot Classification0
Few-Shot Semantic Parsing for New PredicatesCode1
TLRM: Task-level Relation Module for GNN-based Few-Shot Learning0
Improving Few-Shot Learning with Auxiliary Self-Supervised Pretext TasksCode1
Learn from Concepts: Towards the Purified Memory for Few-shot Learning0
Contrastive Prototype Learning with Augmented Embeddings for Few-Shot Learning0
Stress Testing of Meta-learning Approaches for Few-shot Learning0
Few-Shot Bayesian Optimization with Deep Kernel Surrogates0
Cross-domain few-shot learning with unlabelled data0
Machine learning with limited data0
What Makes Good In-Context Examples for GPT-3?Code4
Free Lunch for Few-shot Learning: Distribution CalibrationCode1
Learning to Focus: Cascaded Feature Matching Network for Few-shot Image Recognition0
Lesion2Vec: Deep Metric Learning for Few-Shot Multiple Lesions Recognition in Wireless Capsule Endoscopy Video0
Shallow Bayesian Meta Learning for Real-World Few-Shot RecognitionCode1
Few-Shot Learning with Class ImbalanceCode1
Local Propagation for Few-Shot Learning0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1gpt-4-0125-previewAccuracy61.91Unverified
2gpt-4-0125-previewAccuracy52.49Unverified
3gpt-3.5-turboAccuracy41.48Unverified
4gpt-3.5-turboAccuracy37.06Unverified
5johnsnowlabs/JSL-MedMNX-7BAccuracy25.63Unverified
6yikuan8/Clinical-LongformerAccuracy25.55Unverified
7BioMistral/BioMistral-7B-DAREAccuracy25.06Unverified
8yikuan8/Clinical-LongformerAccuracy25.04Unverified
9PharMolix/BioMedGPT-LM-7BAccuracy24.92Unverified
10PharMolix/BioMedGPT-LM-7BAccuracy24.75Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean67.27Unverified
2SaSPA + CAL4-shot Accuracy48.3Unverified
3Real-Guidance + CAL4-shot Accuracy41.5Unverified
4CAL4-shot Accuracy40.9Unverified
#ModelMetricClaimedVerifiedStatus
1SaSPA + CALHarmonic mean52.2Unverified
2CALHarmonic mean35.2Unverified
3Variational Prompt TuningHarmonic mean34.69Unverified
4Real-Guidance + CALHarmonic mean34.5Unverified
#ModelMetricClaimedVerifiedStatus
1BGNNAccuracy92.7Unverified
2TIM-GDAccuracy87.4Unverified
3UNEM-GaussianAccuracy66.4Unverified
#ModelMetricClaimedVerifiedStatus
1EASY (transductive)Accuracy82.75Unverified
2HCTransformers5 way 1~2 shot74.74Unverified
3HyperShotAccuracy53.18Unverified
#ModelMetricClaimedVerifiedStatus
1SaSPA + CAL4-shot Accuracy66.7Unverified
2Real-Guidance + CAL4-shot Accuracy44.3Unverified
3CAL4-shot Accuracy42.2Unverified
#ModelMetricClaimedVerifiedStatus
1HCTransformersAcc74.74Unverified
2DPGNAcc67.6Unverified
#ModelMetricClaimedVerifiedStatus
1MetaGen Blended RAG (zero-shot)Accuracy77.9Unverified
2CoT-T5-11B (1024 Shot)Accuracy73.42Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean96.44Unverified
#ModelMetricClaimedVerifiedStatus
1CoT-T5-11B (1024 Shot)Accuracy68.3Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean77.71Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean81.12Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean91.57Unverified
#ModelMetricClaimedVerifiedStatus
1CovidExpertAUC-ROC1Unverified
#ModelMetricClaimedVerifiedStatus
1CoT-T5-11B (1024 Shot)Accuracy78.02Unverified
#ModelMetricClaimedVerifiedStatus
1UNEM-GaussianAccuracy65.7Unverified
#ModelMetricClaimedVerifiedStatus
1UNEM-GaussianAccuracy73.2Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean96.82Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean73.07Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean78.51Unverified
#ModelMetricClaimedVerifiedStatus
1UNEM-GaussianAccuracy52.3Unverified
#ModelMetricClaimedVerifiedStatus
1Variational Prompt TuningHarmonic mean79Unverified