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 16511700 of 2964 papers

TitleStatusHype
Few-shot Learning with Noisy LabelsCode1
A Simple Approach to Adversarial Robustness in Few-shot Image ClassificationCode0
MGIMN: Multi-Grained Interactive Matching Network for Few-shot Text Classification0
GDC- Generalized Distribution Calibration for Few-Shot Learning0
Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot ClassificationCode1
BankNote-Net: Open dataset for assistive universal currency recognitionCode1
Interval Bound Interpolation for Few-shot Learning with Few TasksCode0
Powering Finetuning in Few-Shot Learning: Domain-Agnostic Bias Reduction with Selected Sampling0
Universal Representations: A Unified Look at Multiple Task and Domain LearningCode1
PaLM: Scaling Language Modeling with PathwaysCode2
MetaAudio: A Few-Shot Audio Classification BenchmarkCode1
Too Big to Fail? Active Few-Shot Learning Guided Logic SynthesisCode1
PERFECT: Prompt-free and Efficient Few-shot Learning with Language ModelsCode1
AutoProtoNet: Interpretability for Prototypical NetworksCode0
Inverse is Better! Fast and Accurate Prompt for Few-shot Slot TaggingCode1
On the Efficiency of Integrating Self-supervised Learning and Meta-learning for User-defined Few-shot Keyword Spotting0
Selecting task with optimal transport self-supervised learning for few-shot classification0
Leveraging pre-trained language models for conversational information seeking from text0
kNN-NER: Named Entity Recognition with Nearest Neighbor SearchCode1
Overcoming challenges in leveraging GANs for few-shot data augmentationCode1
Supervised Graph Contrastive Learning for Few-shot Node Classification0
WAVPROMPT: Towards Few-Shot Spoken Language Understanding with Frozen Language ModelsCode1
Integrative Few-Shot Learning for Classification and SegmentationCode1
Enabling hand gesture customization on wrist-worn devices0
TraHGR: Transformer for Hand Gesture Recognition via ElectroMyography0
A Framework of Meta Functional Learning for Regularising Knowledge Transfer0
Few-Shot Learning with Siamese Networks and Label TuningCode1
Compare learning: bi-attention network for few-shot learning0
A Rationale-Centric Framework for Human-in-the-loop Machine LearningCode1
Multidimensional Belief Quantification for Label-Efficient Meta-LearningCode0
HyperShot: Few-Shot Learning by Kernel HyperNetworksCode1
Partitioning Image Representation in Contrastive Learning0
Incremental Few-Shot Learning via Implanting and Compressing0
Prototypical Verbalizer for Prompt-based Few-shot TuningCode4
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot LearningCode1
Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot LearningCode1
Few-Shot Learning on Graphs0
In-Context Learning for Few-Shot Dialogue State TrackingCode1
Meta-Learning of NAS for Few-shot Learning in Medical Image Applications0
Label Semantics for Few Shot Named Entity RecognitionCode1
GCT: Graph Co-Training for Semi-Supervised Few-Shot Learning0
Wave-SAN: Wavelet based Style Augmentation Network for Cross-Domain Few-Shot LearningCode0
Deep Transfer Learning with Graph Neural Network for Sensor-Based Human Activity Recognition0
Self-Promoted Supervision for Few-Shot TransformerCode1
Masked Autoencoders for Point Cloud Self-supervised LearningCode2
Worst Case Matters for Few-Shot RecognitionCode1
Rethinking Task Sampling for Few-shot Vision-Language Transfer LearningCode0
InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERCode1
Learning from Few Examples: A Summary of Approaches to Few-Shot Learning0
Pre-trained Token-replaced Detection Model as Few-shot LearnerCode0
Show:102550
← PrevPage 34 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