Meta-Learning

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Overview

Meta-learning studies how experience across related tasks can prepare a model to learn a new task from a small support set, brief feedback, or context alone. Common approaches include gradient-based initialization methods such as MAML, metric and prototype methods, Bayesian methods, learned optimizers and hypernetworks, and episodic training for in-context or test-time adaptation. Applications range from few-shot vision and domain-shifted control to AutoML, scientific system identification, and language or robotic agents, where fast adaptation can reduce labeling, retraining, or optimization costs. The central challenge is transferring useful shared structure without negative transfer: task diversity, distribution shift, uncertainty, costly bilevel training, and fair evaluation of adaptation remain active concerns.

Latest papers

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166 papers20 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. Meta-Learned Adaptive Optimization for Robust Human Mesh Recovery with Uncertainty-Aware Parameter Updates

    Mar 27, 2026Shaurjya Mandal, Nutan Sharma, John GaleottiHuman Mesh RecoveryTest-Time Optimization

  2. Few-Shot Left Atrial Wall Segmentation in 3D LGE MRI via Meta-Learning

    Mar 26, 2026Yusri Al-Sanaani, Rebecca Thornhill, Pablo Nery +5Medical Image Segmentation3D Medical Image Segmentation

    Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada · Department of Radiology, Radiation Oncology, and Medical Physics, University of Ottawa, Ottawa, Canada · Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, Ottawa, Canada

  3. A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks

    Mar 23, 2026Anish Saha, Konstantin ShmakovZero-Shot Time Series ForecastingMeta-Learning

    Walmart Sunnyvale, USA

  4. SOLAR: A Self-Optimizing Open-Ended Autonomous Agent for Lifelong Learning and Continual Adaptation

    Mar 23, 2026Nitin Vetcha, Dianbo LiuContinual Learning for LLM AgentsContinual Learning for LLMs

    Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore · Department of Computational and Data Sciences, Indian Institute of Science, Bangalore, Karnataka, India

  5. Statistical Learning for Latent Embedding Alignment with Application to Brain Encoding and Decoding

    Mar 22, 2026Shuoxun Xu, Zhanhao Yan, Lexin LiLatent Space AlignmentNeural Decoding

    University of California at Berkeley

  6. Meta-Learning for Repeated Bayesian Persuasion

    Mar 20, 2026Ata Poyraz Turna, Asrin Efe Yorulmaz, Tamer BaşarBayesian PersuasionMeta-Learning

    Bogazici University · University of Illinois Urbana–Champaign

  7. Integrating Meta-Features with Knowledge Graph Embeddings for Meta-Learning

    Mar 20, 2026Antonis Klironomos, Ioannis Dasoulas, Francesco Periti +4Meta-LearningAutomated Machine Learning

    Bosch Center for Artificial Intelligence, Germany · University of Mannheim, Germany · KU Leuven, Belgium +3

  8. Bounded Coupled AI Learning Dynamics in Tri-Hierarchical Drone Swarms

    Mar 20, 2026Oleksii BychkovSwarm RoboticsMulti-Agent Reinforcement Learning

    Taras Shevchenko National University of Kyiv

  9. SwiftGS: Episodic Priors for Immediate Satellite Surface Recovery

    Mar 19, 2026Rong Fu, Jiekai Wu, Xiaowen Ma +43D ReconstructionFeed-Forward 3D Reconstruction

    Independent Researcher

  10. Probabilistic Federated Learning on Uncertain and Heterogeneous Data with Model Personalization

    Mar 18, 2026Ratun Rahman, Dinh C. NguyenFederated LearningHeterogeneous Federated Learning

    Department of Electrical and Computer Engineering, University of Alabama in Huntsville, Huntsville, AL 35899, USA

  11. Variational Rectification Inference for Learning with Noisy Labels

    Mar 18, 2026Haoliang Sun, Qi Wei, Lei Feng +4Learning with Noisy LabelsVariational Inference

    School of Software, Shandong University, Jinan, China. · School of Computer Science and Engineering, Nanyang Technological University, Singapore. · School of Computing, National University of Singapore, Singapore. +1

  12. MetaClaw: Just Talk -- An Agent That Meta-Learns and Evolves in the Wild

    Mar 17, 2026Peng Xia, Jianwen Chen, Xinyu Yang +10Continual Learning for LLM AgentsLLM Agent Skill Learning

    UNC-Chapel Hill · Carnegie Mellon University · UC Santa Cruz +1

  13. Learning to Order: Task Sequencing as In-Context Optimization

    Mar 15, 2026Jan Kobiolka, Christian Frey, Arlind Kadra +2Meta-Learning

    Department of Computer Science and Artificial Intelligence, University of Technology Nuremberg, Germany · Department of Computer Science, Albert Ludwig University of Freiburg, Germany

  14. MetaKE: Meta-Learning for Knowledge Editing Toward a Better Accuracy-Editability Trade-off

    Mar 13, 2026Shuxin Liu, Di Gao, Ou WuKnowledge EditingLanguage Model Editing

    Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China

  15. Deployment-Oriented Session-wise Meta-Calibration for Landmark-Based Webcam Gaze Tracking

    Mar 12, 2026Chenkai ZhangGaze EstimationEye Tracking

    Independent Researcher, Wenzhou, Zhejiang 325000, China

  16. MetaDAT: Generalizable Trajectory Prediction via Meta Pre-training and Data-Adaptive Test-Time Updating

    Mar 10, 2026Yuning Wang, Pu Zhang, Yuan He +2Adaptive Learning RateTrajectory Prediction

    State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, IAIR, Xi’an Jiaotong University, China · KargoBot, China

  17. Tactile Recognition of Both Shapes and Materials with Automatic Feature Optimization-Enabled Meta Learning

    Mar 9, 2026Hongliang Zhao, Wenhui Yang, Yang Chen +3Robotic Tactile SensingMeta-Learning

    School of Mechanical Engineering, Southeast University, Nanjing 211189, China. · State Key Laboratory of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing, 10081, China · State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin, 150001, China.

  18. Metalearning traffic assignment for network disruptions with graph convolutional neural networks

    Mar 6, 2026Serio Agriesti, Guido Cantelmo, Francisco Camara PereiraTraffic Flow EstimationIntelligent Transportation Systems

    Department of Technology, Management and Economics, Technical University of Denmark, Lyngby, Denmark

  19. Robust Unscented Kalman Filtering via Recurrent Meta-Adaptation of Sigma-Point Weights

    Mar 4, 2026Kenan Majewski, Michał Modzelewski, Marcin Żugaj +1Unscented Kalman FilteringRobust Estimation

    Institute of Aeronautics and Applied Mechanics, Warsaw University of Technology, Warsaw, Poland

  20. Test-Time Meta-Adaptation with Self-Synthesis

    Mar 3, 2026Zeyneb N. Kaya, Nick RuiInference-Time Adaptation of Language ModelsTest-Time Adaptation

    Stanford University

  21. Boosting Meta-Learning for Few-Shot Text Classification via Label-guided Distance Scaling

    Feb 28, 2026Yunlong Gao, Xinyue Liu, Yingbo Wang +2Few-Shot Text ClassificationText Classification

    Dalian University of Technology, Dalian, China

  22. Relatron: Automating Relational Machine Learning over Relational Databases

    Feb 26, 2026Zhikai Chen, Han Xie, Jian Zhang +3Relational Deep LearningModel Selection

    Michigan State University · Amazon

  23. Meta-FC: Meta-Learning with Feature Consistency for Robust and Generalizable Watermarking

    Feb 25, 2026Yuheng Li, Weitong Chen, Chengcheng Zhu +4Robust WatermarkingMeta-Learning

    Yangzhou University · Nanjing University · Shandong University +2

  24. AHC: Meta-Learned Adaptive Compression for Continual Object Detection on Memory-Constrained Microcontrollers

    Feb 24, 2026Bibin WilsonContinual Object DetectionObject Detection

    Independent Researcher

  25. MAML-KT: Addressing Cold Start Problem in Knowledge Tracing for New Students via Few-Shot Model-Agnostic Meta Learning

    Feb 24, 2026Indronil Bhattacharjee, Christabel WayllaceKnowledge TracingFew-Shot Learning

    New Mexico State University, Las Cruces, New Mexico, USA

  26. Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agent

    Feb 23, 2026Björn Hoppmann, Christoph ScholzMeta-LearningMeta-Reinforcement Learning

  27. Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings

    Feb 23, 2026Lotta Mäkinen, Jorge Loría, Samuel KaskiMeta-LearningOOD Generalization

    Department of Computer Science, Aalto University, Espoo, Finland · ELLIS Institute Finland, Espoo, Finland · Department of Computer Science, University of Manchester, United Kingdom

  28. Celo2: Towards Learned Optimization Free Lunch

    Feb 22, 2026Abhinav Moudgil, Boris Knyazev, Eugene BelilovskyLearning to OptimizeDeep Learning Optimization

    Mila · Concordia University · Samsung AI Lab, Montreal +1

  29. Explaining AutoClustering: Uncovering Meta-Feature Contribution in AutoML for Clustering

    Feb 20, 2026Matheus Camilo da Silva, Leonardo Arrighi, Ana Carolina Lorena +1Automated Machine LearningMeta-Learning

    Department of Mathematics, Computer Science and Geosciences, University of Trieste, Piazzale Europa, 1, 34127 Trieste TS, Italy. · Division of Computer Science, Aeronautics Institute of Technology, Praça Marechal Eduardo Gomes, 50, 12228-900 São José dos Campos SP, Brazil.

  30. Adapting Actively on the Fly: Relevance-Guided Online Meta-Learning with Latent Concepts for Geospatial Discovery

    Feb 19, 2026Jowaria Khan, Anindya Sarkar, Yevgeniy Vorobeychik +1Adaptive SamplingActive Learning

    University of Michigan, Ann Arbor, MI, USA · Washington University in St. Louis, St. Louis, MO, USA