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 11011150 of 2964 papers

TitleStatusHype
Exploring the Space of Key-Value-Query Models with Intention0
MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer TasksCode1
Large Language Models Leverage External Knowledge to Extend Clinical Insight Beyond Language Boundaries0
CPL-NoViD: Context-Aware Prompt-based Learning for Norm Violation Detection in Online CommunitiesCode0
RAMario: Experimental Approach to Reptile Algorithm -- Reinforcement Learning for MarioCode0
Learning More Discriminative Local Descriptors for Few-shot Learning0
SuSana Distancia is all you need: Enforcing class separability in metric learning via two novel distance-based loss functions for few-shot image classification0
Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal PerspectivesCode1
Meta-DM: Applications of Diffusion Models on Few-Shot Learning0
Meta Omnium: A Benchmark for General-Purpose Learning-to-LearnCode1
CodeIE: Large Code Generation Models are Better Few-Shot Information ExtractorsCode1
Few Shot Learning for Medical Imaging: A Comparative Analysis of Methodologies and Formal Mathematical Framework0
The Role of Data Curation in Image CaptioningCode0
Joint Graph Learning and Model Fitting in Laplacian Regularized Stratified ModelsCode0
Alleviating Exposure Bias via Multi-level Contrastive Learning and Deviation Simulation in Abstractive SummarizationCode0
Learning to Detect Novel and Fine-Grained Acoustic Sequences Using Pretrained Audio Representations0
Plug-and-Play Multilingual Few-shot Spoken Words Recognition0
Causal Interventions-based Few-Shot Named Entity Recognition0
DocLangID: Improving Few-Shot Training to Identify the Language of Historical DocumentsCode0
AttenWalker: Unsupervised Long-Document Question Answering via Attention-based Graph WalkingCode0
Parameter-Efficient Cross-lingual Transfer of Vision and Language Models via Translation-based AlignmentCode0
Accelerating Neural Self-Improvement via Bootstrapping0
Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual NoiseCode1
Multistage Relation Network With Dual-Metric for Few-Shot Hyperspectral Image ClassificationCode1
HQP: A Human-Annotated Dataset for Detecting Online PropagandaCode0
Analogy-Forming Transformers for Few-Shot 3D Parsing0
Adaptive manifold for imbalanced transductive few-shot learning0
ESPT: A Self-Supervised Episodic Spatial Pretext Task for Improving Few-Shot LearningCode1
Context-enriched molecule representations improve few-shot drug discoveryCode1
Towards Addressing Training Data Scarcity Challenge in Emerging Radio Access Networks: A Survey and Framework0
Meta-tuning Loss Functions and Data Augmentation for Few-shot Object Detection0
Transductive Few-shot Learning with Prototype-based Label Propagation by Iterative Graph RefinementCode1
Semantic-Aware Graph Matching Mechanism for Multi-Label Image RecognitionCode0
RPLKG: Robust Prompt Learning with Knowledge Graph0
Information Extraction from Documents: Question Answering vs Token Classification in real-world setups0
Clustered-patch Element Connection for Few-shot LearningCode0
MasakhaNEWS: News Topic Classification for African languagesCode1
MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning0
Few-shot Medical Image Segmentation via Cross-Reference Transformer0
CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models0
A Survey on Few-Shot Class-Incremental Learning0
The Art of Camouflage: Few-Shot Learning for Animal Detection and SegmentationCode0
Instance-level Few-shot Learning with Class Hierarchy MiningCode0
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with TextCode2
SMAE: Few-shot Learning for HDR Deghosting with Saturation-Aware Masked Autoencoders0
LSFSL: Leveraging Shape Information in Few-shot Learning0
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence0
Out-of-distribution Few-shot Learning For Edge Devices without Model Fine-tuning0
GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot LearningCode1
Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges0
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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