SOTAVerified

Meta-Learning

Meta-learning is a methodology considered with "learning to learn" machine learning algorithms.

( Image credit: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1821–1830 of 3569 papers

TitleStatusHype
DAML-ST5: Low Resource Style Transfer via Domain Adaptive Meta Learning—0
Unsupervised Domain Adaptation for Event Detection via Meta Self-Paced Learning—0
DAML: Chinese Named Entity Recognition with a fusion method of data-augmentation and meta-learning—0
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis—0
Persian Natural Language Inference: A Meta-learning approach—0
MAML-CL: Edited Model-Agnostic Meta-Learning for Continual LearningCode0
Meta-Adapter: Parameter Efficient Few-Shot Learning through Meta-Learning—0
Learn to Adapt for Generalized Zero-Shot Text Classification—0
A Self-Adaptive Learning Rate and Curriculum Learning Based Framework for Few-Shot Text Classification—0
Online Meta Adaptation for Variable-Rate Learned Image Compression—0
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All datasetsML10MT50ML45OMNIGLOT - 1-Shot, 20-way

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-train success rate97.8—Unverified
2MZMeta-train success rate97.6—Unverified
3MAMLMeta-test success rate36—Unverified
4RL^2Meta-test success rate10—Unverified
5DnCMeta-test success rate5.4—Unverified
6PEARLMeta-test success rate0—Unverified
#ModelMetricClaimedVerifiedStatus
1SoftModuleAverage Success Rate60—Unverified
2Multi-task multi-head SACAverage Success Rate35.85—Unverified
3DisCorAverage Success Rate26—Unverified
4NDPAverage Success Rate11—Unverified
#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-test success rate (zero-shot)18.5—Unverified
2MZMeta-test success rate (zero-shot)17.7—Unverified
#ModelMetricClaimedVerifiedStatus
1Metadrop% Test Accuracy95.75—Unverified