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 24512500 of 2964 papers

TitleStatusHype
How to trust unlabeled data? Instance Credibility Inference for Few-Shot LearningCode1
Concept Learners for Few-Shot LearningCode1
Attentive Graph Neural Networks for Few-Shot Learning0
Towards Cross-Granularity Few-Shot Learning: Coarse-to-Fine Pseudo-Labeling with Visual-Semantic Meta-Embedding0
Generalized Few-Shot Video Classification with Video Retrieval and Feature GenerationCode1
Wandering Within a World: Online Contextualized Few-Shot LearningCode1
Online probabilistic label treesCode1
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and DatasetsCode1
Few-Shot One-Class Classification via Meta-LearningCode1
Predicting the Accuracy of a Few-Shot ClassifierCode0
Meta-Learning with Network Pruning0
Learning to learn generative programs with Memoised Wake-Sleep0
Meta-Learning Divergences of Variational Inference0
Covariate Distribution Aware Meta-learningCode1
MetaConcept: Learn to Abstract via Concept Graph for Weakly-Supervised Few-Shot Learning0
A Revision of Neural Tangent Kernel-based Approaches for Neural Networks0
Few-Shot Microscopy Image Cell SegmentationCode1
Improving Few-Shot Learning using Composite Rotation based Auxiliary Task0
Laplacian Regularized Few-Shot LearningCode1
Many-Class Few-Shot Learning on Multi-Granularity Class HierarchyCode1
Laplacian Regularized Few-Shot LearningCode1
Global Convergence and Generalization Bound of Gradient-Based Meta-Learning with Deep Neural NetsCode2
Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation0
Discrete Few-Shot Learning for Pan Privacy0
Graph Prototypical Networks for Few-shot Learning on Attributed NetworksCode1
Generalized Zero and Few-Shot Transfer for Facial Forgery Detection0
Deep Double-Side Learning Ensemble Model for Few-Shot Parkinson Speech Recognition0
Self-Supervised Prototypical Transfer Learning for Few-Shot ClassificationCode1
Predictive Complexity Priors0
Enhancing Few-Shot Image Classification with Unlabelled Examples0
Extensively Matching for Few-shot Learning Event DetectionCode0
Self-supervised Knowledge Distillation for Few-shot LearningCode1
Towards an Unsupervised Method for Model Selection in Few-Shot Learning0
Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data0
LFD-ProtoNet: Prototypical Network Based on Local Fisher Discriminant Analysis for Few-shot Learning0
Graph Meta Learning via Local SubgraphsCode1
Few-shot Object Detection on Remote Sensing Images0
Meta-Learning GNN Initializations for Low-Resource Molecular Property Prediction0
Tackling Non-forgetting and Forward Transfer with a Unified Lifelong Learning Approach0
Learning to Learn Kernels with Variational Random FeaturesCode0
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection NetworkCode1
Simultaneous Perturbation Stochastic Approximation for Few-Shot Learning0
A Transductive Multi-Head Model for Cross-Domain Few-Shot LearningCode0
Calibrated neighborhood aware confidence measure for deep metric learning0
Ensemble Model with Batch Spectral Regularization and Data Blending for Cross-Domain Few-Shot Learning with Unlabeled DataCode0
Multi-step Estimation for Gradient-based Meta-learning0
Unsupervised Transfer Learning with Self-Supervised Remedy0
Multi-view Contrastive Learning for Online Knowledge DistillationCode1
Distributionally Robust Weighted k-Nearest Neighbors0
Leveraging the Feature Distribution in Transfer-based Few-Shot LearningCode1
Show:102550
← PrevPage 50 of 60Next →

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