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 76100 of 3569 papers

TitleStatusHype
What Do Language Models Learn in Context? The Structured Task HypothesisCode1
GS-Phong: Meta-Learned 3D Gaussians for Relightable Novel View SynthesisCode1
Learning to Continually Learn with the Bayesian PrincipleCode1
HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement LearningCode1
Towards Foundation Model for Chemical Reactor Modeling: Meta-Learning with Physics-Informed AdaptationCode1
Adapting to Distribution Shift by Visual Domain Prompt GenerationCode1
Chameleon: A Data-Efficient Generalist for Dense Visual Prediction in the WildCode1
SOPHON: Non-Fine-Tunable Learning to Restrain Task Transferability For Pre-trained ModelsCode1
Efficient Automatic Tuning for Data-driven Model Predictive Control via Meta-LearningCode1
NTK-Guided Few-Shot Class Incremental LearningCode1
Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated ExpertsCode1
Harnessing Meta-Learning for Improving Full-Frame Video StabilizationCode1
On Latency Predictors for Neural Architecture SearchCode1
Fast and Efficient Local Search for Genetic Programming Based Loss Function LearningCode1
Diffusion-Based Neural Network Weights GenerationCode1
Reinforced In-Context Black-Box OptimizationCode1
Discovering Temporally-Aware Reinforcement Learning AlgorithmsCode1
Is Mamba Capable of In-Context Learning?Code1
Symbol: Generating Flexible Black-Box Optimizers through Symbolic Equation LearningCode1
A Survey of Few-Shot Learning on Graphs: from Meta-Learning to Pre-Training and Prompt LearningCode1
Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real WorldCode1
Positive-Unlabeled Learning by Latent Group-Aware Meta DisambiguationCode1
Selective-Memory Meta-Learning with Environment Representations for Sound Event Localization and DetectionCode1
Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype EnhancementCode1
Discovering modular solutions that generalize compositionallyCode1
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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