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 28012850 of 2964 papers

TitleStatusHype
Few-Shot NLG with Pre-Trained Language ModelCode0
Hierarchical Meta Learning0
An Ensemble of Epoch-wise Empirical Bayes for Few-shot LearningCode0
Few Shot Speaker Recognition using Deep Neural Networks0
TAFE-Net: Task-Aware Feature Embeddings for Low Shot LearningCode0
Synthetic Examples Improve Generalization for Rare Classes0
Generalizing from a Few Examples: A Survey on Few-Shot LearningCode0
Large-Scale Long-Tailed Recognition in an Open WorldCode1
Few-Shot Learning with Localization in Realistic SettingsCode0
L2AE-D: Learning to Aggregate Embeddings for Few-shot Learning with Meta-level Dropout0
Semi-Supervised Few-Shot Learning for Dual Question-Answer Extraction0
A Closer Look at Few-shot ClassificationCode1
Meta-Learning with Differentiable Convex OptimizationCode1
Few-Shot Learning via Saliency-guided Hallucination of Samples0
A Hybrid Approach with Optimization and Metric-based Meta-Learner for Few-Shot Learning0
Hyperbolic Image EmbeddingsCode1
Revisiting Local Descriptor based Image-to-Class Measure for Few-shot LearningCode0
Diversity with Cooperation: Ensemble Methods for Few-Shot ClassificationCode0
Few-Shot Regression via Learned Basis Functions0
f-VAEGAN-D2: A Feature Generating Framework for Any-Shot Learning0
Learning from Adversarial Features for Few-Shot Classification0
Few-Shot Learning-Based Human Activity Recognition0
Learning To Avoid Negative Transfer in Few Shot Transfer Learning0
Cross-Linked Variational Autoencoders for Generalized Zero-Shot Learning0
Multi-Class Few Shot Learning Task and Controllable Environment0
Dense Classification and Implanting for Few-Shot Learning0
GOGGLES: Automatic Image Labeling with Affinity CodingCode0
Interpreting and Understanding Graph Convolutional Neural Network using Gradient-based Attribution Method0
Reproducibility and Stability Analysis in Metric-Based Few-Shot Learning0
CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot LearningCode0
Semi-Supervised Few-Shot Learning with Prototypical Random WalksCode0
Unsupervised Attention Mechanism across Neural Network LayersCode0
LaSO: Label-Set Operations networks for multi-label few-shot learningCode0
Assume, Augment and Learn: Unsupervised Few-Shot Meta-Learning via Random Labels and Data Augmentation0
Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency ParsingCode0
Are Few-Shot Learning Benchmarks too Simple ? Solving them without Task Supervision at Test-TimeCode0
Adaptive Cross-Modal Few-Shot LearningCode0
Infinite Mixture Prototypes for Few-Shot Learning0
Meta-CurvatureCode0
Adaptive Posterior Learning: few-shot learning with a surprise-based memory moduleCode0
Centroid-based deep metric learning for speaker recognition0
'Squeeze & Excite' Guided Few-Shot Segmentation of Volumetric ImagesCode1
tax2vec: Constructing Interpretable Features from Taxonomies for Short Text ClassificationCode0
Massively Multilingual Transfer for NERCode0
Few-shot Learning with Meta Metric Learners0
BioBERT: a pre-trained biomedical language representation model for biomedical text miningCode1
Learning Classifiers for Domain Adaptation, Zero and Few-Shot Recognition Based on Learning Latent Semantic Parts0
Sequential Skip Prediction with Few-shot in Streamed Music ContentsCode0
Human few-shot learning of compositional instructionsCode1
FIGR: Few-shot Image Generation with ReptileCode0
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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