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 61–70 of 3569 papers

TitleStatusHype
LoRA Recycle: Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAsCode1
EEG-Reptile: An Automatized Reptile-Based Meta-Learning Library for BCIsCode1
Personalized Dynamic Music Emotion Recognition with Dual-Scale Attention-Based Meta-LearningCode1
Unlocking Tuning-Free Few-Shot Adaptability in Visual Foundation Models by Recycling Pre-Tuned LoRAsCode1
Task-Aware Harmony Multi-Task Decision Transformer for Offline Reinforcement LearningCode1
Amortized Probabilistic Conditioning for Optimization, Simulation and InferenceCode1
Metalic: Meta-Learning In-Context with Protein Language ModelsCode1
PersonalLLM: Tailoring LLMs to Individual PreferencesCode1
Can Learned Optimization Make Reinforcement Learning Less Difficult?Code1
Nonrigid Reconstruction of Freehand Ultrasound without a TrackerCode1
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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