Online Continual Learning

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Overview

Online continual learning studies how models can learn from data as it arrives, often in a single pass and without known task boundaries, while retaining useful information from the past. Common approaches use replay buffers or structured memories, constrain updates with regularization or parameter-efficient adapters, expand model capacity, or detect distribution shifts to trigger targeted updates. Researchers evaluate these methods on streaming vision and language tasks, time-series drift, robotics, and resource-constrained devices, measuring accuracy, forgetting, transfer, memory, and compute. A central challenge is balancing adaptation to new or recurring patterns against retention, while ensuring results hold under realistic streams and do not depend on hidden assumptions such as task labels or pretrained features.

Latest papers

CardsList

106 papers18 papers in the last four weeks, up 80% on the four weeks before. 0.1% of all new papers.

  1. TALON: Test-time Adaptive Learning for On-the-Fly Category Discovery

    Mar 9, 2026Yanan Wu, Yuhan Yan, Tailai Chen +5Test-Time AdaptationPrototype-Based Classification

    College of Information and Electrical Engineering, China Agricultural University, China · College of Science, China Agricultural University, China · Woof RoboT Co., Ltd., China +4

  2. Online Continual Learning for Anomaly Detection in IoT under Data Distribution Shifts

    Mar 8, 2026Matea Marinova, Shashi Raj Pandey, Junya Shiraishi +3Continual Anomaly DetectionOnline Anomaly Detection

    Faculty of Electrical Engineering and Information Technologies, Ss. Cyril and Methodius University in Skopje, 1000 Skopje, North Macedonia · Dept. of Electronic Systems, Aalborg University, Aalborg, Denmark

  3. Context Channel Capacity: An Information-Theoretic Framework for Understanding Catastrophic Forgetting

    Mar 8, 2026Ran ChengCatastrophic ForgettingOnline Continual Learning

  4. Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams

    Mar 8, 2026Jiyeon Kim, Hyunji Lee, Dylan Zhou +6LLM EvaluationContinual Learning for LLMs

    KAIST AI · UNC Chapel Hill · Google +3

  5. When and Where to Reset Matters for Long-Term Test-Time Adaptation

    Mar 4, 2026Taejun Lim, Joong-Won Hwang, Kibok LeeTest-Time AdaptationContinual Test-Time Adaptation

    1Yonsei University · 2ETRI

  6. cPNN: Continuous Progressive Neural Networks for Evolving Streaming Time Series

    Mar 3, 2026Federico Giannini, Giacomo Ziffer, Emanuele Della ValleOnline Continual LearningConcept Drift

    DEIB, Politecnico di Milano, Milano, Italy

  7. Streaming Continual Learning for Unified Adaptive Intelligence in Dynamic Environments

    Mar 2, 2026Federico Giannini, Giacomo Ziffer, Andrea Cossu +1Continual LearningOnline Continual Learning

    DEIB, Politecnico di Milano, Milano, 20133, Italy · Computer Science Department, University of Pisa, Pisa, Italy

  8. FastODT: A tree-based framework for efficient continual learning

    Feb 27, 2026Daniel Bretsko, Piotr Walas, Devashish Khulbe +3Online Continual LearningDecision Tree Learning

    Masaryk University, Brno, Czech Republic · Warsaw University of Technology, Warsaw, Poland · Mycroft Mind, Brno, Czech Republic +2

  9. Unsupervised Continual Learning for Amortized Bayesian Inference

    Feb 26, 2026Aayush Mishra, Šimon Kucharský, Paul-Christian BürknerAmortized InferenceOnline Continual Learning

    Department of Statistics, TU Dortmund University, Germany

  10. Learning During Detection: Continual Learning for Neural OFDM Receivers via DMRS

    Feb 23, 2026Mohanad Obeed, Ming JianWireless CommunicationsOnline Continual Learning

    Advanced Wireless Technology Lab, Huawei Technologies Canada Co. Ltd, ON K2K 3J1, Canada

  11. Representation Stability in a Minimal Continual Learning Agent

    Feb 23, 2026Vishnu SubramanianContinual LearningLifelong Learning Agents

    AI/ML Computational Science Associate Manager, Accenture

  12. Are Current Continual Learning Methods Truly Agnostic? Introducing OPRE, a Step Toward Agnostic Continual Learning

    Nov 11, 2025Raphaël Bayle, Martial Mermillod, Robert M. FrenchContinual LearningCoreset Selection

    Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, CNRS, LPNC, Grenoble, France · LEAD-CNRS UMR 5022, U. de Bourgogne Europe, Dijon, France

  13. Online Continual Learning on Intel Loihi 2 via a Co-designed Spiking Neural Network

    Nov 3, 2025Elvin Hajizada, Danielle Rager, Timothy Shea +5Online Continual LearningIncremental Learning

    Institute of Informatics, University of Munich (LMU), Munich, Germany · Intel Labs, Intel Corporation, Santa Clara, CA, USA · Southwest Research Institute, San Antonio, TX, USA +3

  14. Local Timescale Gates for Timescale-Robust Continual Spiking Neural Networks

    Oct 13, 2025Devansh Deep, Ansh Tiwari, Ayush ChauhanSpiking Neural NetworksOnline Continual Learning

  15. TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree

    Jun 12, 2025Yu-Yang Qian, Yuan-Ze Xu, Zhen-Yu Zhang +2Continual Learning for LLMsLow-Rank Adaptation

    National Key Laboratory for Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China · RIKEN AIP, Tokyo, Japan

  16. AIR: Analytic Imbalance Rectifier for Continual Learning

    Aug 19, 2024Di Fang, Yinan Zhu, Zhiping Lin +3Class-Imbalanced LearningClass-Incremental Learning

    School of Future Technology, South China University of Technology, Guangzhou, China · Shien-Ming Wu School of Intelligent Engineering, South China University of Technology, Guangzhou, China