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 23012350 of 2964 papers

TitleStatusHype
Improving Few-shot Learning with Weakly-supervised Object Localization0
Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling0
Semi-Supervised Few-Shot Classification with Deep Invertible Hybrid Models0
Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning0
Compositional Fine-Grained Low-Shot Learning0
Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection0
HetMAML: Task-Heterogeneous Model-Agnostic Meta-Learning for Few-Shot Learning Across Modalities0
Livewired Neural Networks: Making Neurons That Fire Together Wire Together0
Semi-supervised Contrastive Learning with Similarity Co-calibration0
Ensemble Making Few-Shot Learning Stronger0
Exploring the Similarity of Representations in Model-Agnostic Meta-LearningCode0
Distribution Matching for Heterogeneous Multi-Task Learning: a Large-scale Face Study0
MetaKernel: Learning Variational Random Features with Limited LabelsCode0
Comprehensive Study: How the Context Information of Different Granularity Affects Dialogue State Tracking?Code0
Few-Shot Learning for Image Classification of Common FloraCode0
PEMNET: A Transfer Learning-based Modeling Approach of High-Temperature Polymer Electrolyte Membrane Electrochemical Systems0
Few-shot Partial Multi-view Learning0
Local descriptor-based multi-prototype network for few-shot Learning0
How Fine-Tuning Allows for Effective Meta-Learning0
One Model to Rule them All: Towards Zero-Shot Learning for Databases0
A Deep Learning Framework for Lifelong Machine Learning0
Rich Semantics Improve Few-shot Learning0
Demystification of Few-shot and One-shot Learning0
Self-Supervised WiFi-Based Activity Recognition0
Few-shot learning via tensor hallucinationCode0
Few-shot Learning for Topic Modeling0
Few-shot Continual Learning: a Brain-inspired Approach0
Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot LearningCode0
Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes0
Multilingual and Cross-Lingual Intent Detection from Spoken Data0
Pareto Self-Supervised Training for Few-Shot Learning0
Does language help generalization in vision models?Code0
Memorisation versus Generalisation in Pre-trained Language ModelsCode0
Embedding Adaptation is Still Needed for Few-Shot Learning0
On Unifying Misinformation DetectionCode0
Contextual HyperNetworks for Novel Feature Adaptation0
Few-shot Intent Classification and Slot Filling with Retrieved Examples0
Meta-Learning for Fast Cross-Lingual Adaptation in Dependency ParsingCode0
Reinforced Attention for Few-Shot Learning and Beyond0
Towards Enabling Meta-Learning from Target ModelsCode0
Few-Shot Action Recognition with Compromised Metric via Optimal Transport0
Comparing Transfer and Meta Learning Approaches on a Unified Few-Shot Classification Benchmark0
Efficient Personalized Speech Enhancement through Self-Supervised Learning0
Story Centaur: Large Language Model Few Shot Learning as a Creative Writing Tool0
Modular Adaptation for Cross-Domain Few-Shot LearningCode0
Federated Few-Shot Learning with Adversarial Learning0
Towards Offensive Language Identification for Dravidian LanguagesCode0
Few-shot learning through contextual data augmentationCode0
Head2HeadFS: Video-based Head Reenactment with Few-shot Learning0
Explaining Representation by Mutual Information0
Show:102550
← PrevPage 47 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