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

Showing 776800 of 3569 papers

TitleStatusHype
RedCoast: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUsCode1
Modality-Agnostic Self-Supervised Learning with Meta-Learned Masked Auto-EncoderCode1
Amortised Inference in Neural Networks for Small-Scale Probabilistic Meta-Learning0
RAPL: A Relation-Aware Prototype Learning Approach for Few-Shot Document-Level Relation ExtractionCode1
Deceptive Fairness Attacks on Graphs via Meta LearningCode0
Knowledge-driven Meta-learning for CSI Feedback0
Bayesian Active Learning in the Presence of Nuisance Parameters0
Meta learning with language models: Challenges and opportunities in the classification of imbalanced textCode0
Implicit meta-learning may lead language models to trust more reliable sourcesCode1
Are LSTMs Good Few-Shot Learners?Code0
Towards Subject Agnostic Affective Emotion Recognition0
Meta-learning of Physics-informed Neural Networks for Efficiently Solving Newly Given PDEs0
Unsupervised Representation Learning to Aid Semi-Supervised Meta LearningCode0
Solving Expensive Optimization Problems in Dynamic Environments with Meta-learningCode0
Are Structural Concepts Universal in Transformer Language Models? Towards Interpretable Cross-Lingual GeneralizationCode0
Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal MechanismsCode0
Group Preference Optimization: Few-Shot Alignment of Large Language ModelsCode1
Context-Aware Meta-LearningCode1
Revisiting Logistic-softmax Likelihood in Bayesian Meta-Learning for Few-Shot ClassificationCode1
BioAct-Het: A Heterogeneous Siamese Neural Network for Bioactivity Prediction Using Novel Bioactivity RepresentatioCode0
AMAGO: Scalable In-Context Reinforcement Learning for Adaptive AgentsCode1
Dynamic Link Prediction for New Nodes in Temporal Graph Networks0
A Partially Supervised Reinforcement Learning Framework for Visual Active SearchCode0
Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks0
Subspace Adaptation Prior for Few-Shot LearningCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-train success rate97.8Unverified
2MZMeta-train success rate97.6Unverified
3MAMLMeta-test success rate36Unverified
4RL^2Meta-test success rate10Unverified
5DnCMeta-test success rate5.4Unverified
6PEARLMeta-test success rate0Unverified
#ModelMetricClaimedVerifiedStatus
1SoftModuleAverage Success Rate60Unverified
2Multi-task multi-head SACAverage Success Rate35.85Unverified
3DisCorAverage Success Rate26Unverified
4NDPAverage Success Rate11Unverified
#ModelMetricClaimedVerifiedStatus
1MZ+ReconMeta-test success rate (zero-shot)18.5Unverified
2MZMeta-test success rate (zero-shot)17.7Unverified
#ModelMetricClaimedVerifiedStatus
1Metadrop% Test Accuracy95.75Unverified