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 201250 of 2964 papers

TitleStatusHype
Adversarial Feature Augmentation for Cross-domain Few-shot ClassificationCode1
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain SearchCode1
Adversarial Feature Hallucination Networks for Few-Shot LearningCode1
CodeIE: Large Code Generation Models are Better Few-Shot Information ExtractorsCode1
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With SupervoxelsCode1
Anomaly Detection of Defect using Energy of Point Pattern Features within Random Finite Set FrameworkCode1
Bridging Few-Shot Learning and Adaptation: New Challenges of Support-Query ShiftCode1
Federated Few-Shot Learning for Mobile NLPCode1
AdaptKeyBERT: An Attention-Based approach towards Few-Shot & Zero-Shot Domain Adaptation of KeyBERTCode1
FewCLUE: A Chinese Few-shot Learning Evaluation BenchmarkCode1
An Overview of Deep Learning Architectures in Few-Shot Learning DomainCode1
Anti-aliasing Semantic Reconstruction for Few-Shot Semantic SegmentationCode1
Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled DataCode1
Few-Shot and Continual Learning with Attentive Independent MechanismsCode1
Few-shot Classification via Adaptive AttentionCode1
Few-Shot Class-Incremental Learning via Training-Free Prototype CalibrationCode1
Few-Shot Document-Level Relation ExtractionCode1
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical NetworksCode1
A Prompt Learning Framework for Source Code SummarizationCode1
Concept Learners for Few-Shot LearningCode1
Compressing Lengthy Context With UltraGistCode1
Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpaCode1
A Rationale-Centric Framework for Human-in-the-loop Machine LearningCode1
A Few-shot Learning Approach for Historical Ciphered Manuscript RecognitionCode1
EASE: Unsupervised Discriminant Subspace Learning for Transductive Few-Shot LearningCode1
CoNeRF: Controllable Neural Radiance FieldsCode1
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIsCode1
Context-Transformer: Tackling Object Confusion for Few-Shot DetectionCode1
Context-enriched molecule representations improve few-shot drug discoveryCode1
Few-Shot Learning with a Strong TeacherCode1
A Modern Self-Referential Weight Matrix That Learns to Modify ItselfCode1
Few-shot Learning with Noisy LabelsCode1
Few-Shot Learning with Siamese Networks and Label TuningCode1
Artistic Glyph Image Synthesis via One-Stage Few-Shot LearningCode1
AdapterHub Playground: Simple and Flexible Few-Shot Learning with AdaptersCode1
Contextual Squeeze-and-Excitation for Efficient Few-Shot Image ClassificationCode1
Few-Shot Microscopy Image Cell SegmentationCode1
Few-Shot Named Entity Recognition: A Comprehensive StudyCode1
A Simple Exponential Family Framework for Zero-Shot LearningCode1
A Closer Look at Few-Shot 3D Point Cloud ClassificationCode1
Replication: Contrastive Learning and Data Augmentation in Traffic Classification Using a Flowpic Input RepresentationCode1
AskIt: Unified Programming Interface for Programming with Large Language ModelsCode1
Domain Generalizer: A Few-shot Meta Learning Framework for Domain Generalization in Medical ImagingCode1
Can Explanations Be Useful for Calibrating Black Box Models?Code1
Few-shot Open-set Recognition by Transformation ConsistencyCode1
FewshotQA: A simple framework for few-shot learning of question answering tasks using pre-trained text-to-text modelsCode1
A Closer Look at Few-shot ClassificationCode1
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identificationCode1
COVID-19 detection from scarce chest x-ray image data using few-shot deep learning approachCode1
Boosting on the shoulders of giants in quantum device calibrationCode1
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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