Online Continual Learning

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12 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

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Latest papers 46

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Frozen Models, Evolving Expertise: Model-Agnostic Learning from Deployment Experience for Multimodal Medical AI
Oct 6, 2026Yexiao He, Yucheng Tang, Pengfei Guo +6Medical LLMs Continual Learning for VLMs
University of Maryland, College Park · NVIDIA
Benchmarking Label-Revealed Online Updates for EEG BCI Decoding
Oct 5, 2026Bogdan Kozyrskiy, Artem Grachev, Abraham I. Camelo GuerreroBrain-Computer Interfaces EEG Decoding
Independent Researcher, France · Independent Researcher, Germany · School of Information Technology, York University, Toronto, Canada
LiLib: Lifelong Air-to-Ground Path-Loss Prediction on UAVs via a Drift-Triggered Model Library
Oct 5, 2026Minh TranConcept Drift Wireless Communications
Hanoi University of Science and Technology (HUST), Hanoi, Vietnam
Task Vector Descent: Learning from Non-IID Batches
Oct 4, 2026Anton Baumann, Jonas Hübotter, Zeynep Akata +1Continual Learning for LLMs Task Arithmetic
ETH Zurich · Technical University of Munich
Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations
Oct 1, 2026Giulio Schiavi, Andrei Cramariuc, Michael Pantic +1Robotic Grasping Continual Robot Learning
Autonomous Systems Lab ETH Zurich, Switzerland · Robotics Systems Lab ETH Zurich, Switzerland
A Dynamical Theory of LoRA in Continual Learning
Sep 30, 2026Théo Marchetta, Filippo Alessandroni, Alessandro Breccia +2Continual Learning Low-Rank Adaptation
Department of Mathematics, Alma Mater Studiorum – Università di Bologna, Piazza di Porta San Donato 5, 40126 Bologna, Italy · Gatsby Computational Neuroscience Unit, University College London · Donders Centre for Neuroscience, Radboud University, Nijmegen, The Netherlands
HiTS-CL: A Continual Learning Framework for Long-Horizon Temporal Knowledge Graph Extrapolation
Sep 29, 2026Yansong Liu, Rui Liu, Yuan Zuo +6Temporal Link Prediction Replay-Based Continual Learning
Beihang University Beijing, China · Beijing University of Posts and Telecommunications Beijing, China · Hubei Engineering University Xiaogan, Hubei, China
Online Versatile Incremental Learning: Towards Class and Domain-Agnostic Adaptation at Any Time
Sep 29, 2026Jae-Ho Lee, Min-Yeong Park, Jun-Yeong Moon +2Class-Incremental Learning Domain-Incremental Learning
Korea University, Seoul, Republic of Korea · Kyung Hee University, Yongin, Republic of Korea
Reliable Replay through Spatial Coherence in Online Continual Learning
Sep 27, 2026Haixiang Sun, Jiefu Zhang, Yinghao He +4Continual Learning for LLMs Experience Replay
Purdue University West Lafayette, IN 47907, USA
An Analysis of Streaming Deep Reinforcement Learning for Adaptive Continual Learning in Robotics
Sep 23, 2026Teeratham Vitchutripop, Alyssa Quarles, Wenhe Zhang +2Reinforcement Learning Continual Robot Learning
Department of Computer Science, Yale University, New Haven, CT 06520, USA
TM-APR: Thermal Temporal-Memory Localization via Analytic Online Adaptation
Sep 22, 2026Yanshuo Bai, Kanji TanakaClass-Incremental Learning Visual Place Recognition
Beyond Class Marginals: Bounding Rehearsal Gaps without Freezing Class Co-occurrence
Sep 22, 2026Congren Dai, Nat Roongjirarat, Fei YeClass-Incremental Learning Replay-Based Continual Learning
Imperial College London · King’s College London · University of Electronic Science and Technology of China
Brain-Inspired Hierarchical Modularity for General Continual Learning
Sep 21, 2026Hongwei Yan, Kanglei Zhou, Qi Cheng +7Continual Learning for LLMs Continual Learning for VLA Models
School of Life Sciences, Tsinghua University, Beijing, China. · IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China. · Tsinghua-Peking Center for Life Sciences, Beijing, China. +2
Stable Unsupervised Continual Chunking with Sheaf SyncMap
Sep 21, 2026Xueyuan Li, Danilo Vasconcellos VargasSheaf Neural Networks Online Continual Learning
Self-Evolving Memory for Generative Recommendation
Sep 14, 2026Xinyu Lin, Zhuosong Jiang, Zixiao Suo +12Memory-Augmented Neural Networks Recommender Systems
National University of Singapore · Meta AI
Incremental Evaluation and Training in Relational Deep Learning
Aug 13, 2026Jakub Peleška, Gustav ŠírConcept Drift Online Continual Learning
Czech Technical University in Prague
MAUPITI: On-Device Prototype-Based Learning on a Smart Infrared Sensor
Aug 7, 2026Beatrice Alessandra Motetti, Tanguy Dugas du Villard, Matteo Risso +7Prototype-Based Classification On-Device Training
Politecnico di Torino, Turin, Italy · STMicroelectronics, Cornaredo, Italy
An active-learning framework for real-time depth perception from monocular vision streams
Aug 5, 2026Xiaorong Zeng, Weiqiang Chen, Peng Shi +4Edge Inference Monocular Depth Estimation
School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen, Fujian 361024, China · King Long United Automotive Industry Co. Ltd., Xiamen 361023, China · School of Electrical and Electronic Engineering, The University of Adelaide, Adelaide, SA 5005, Australia +2
Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations
Aug 5, 2026Xujia Chen, Xinyue Hu, Letian Chen +2PDE Surrogate Modeling Replay-Based Continual Learning
Department of Automation, Tsinghua University, Beijing, 100084, China
KC-Agent: A Dual-Process Cognitive Architecture for Efficient ML Model Improvement
Aug 3, 2026Gusseppe Bravo-Rocca, Jordi Guitart, Ajay Dholakia +2Cognitive Modeling Concept Drift
Barcelona Supercomputing Center, Barcelona, Spain · Cotiviti, South Jordan, UT, United States · Universitat Polit`ecnica de Catalunya, Barcelona, Spain +1
Plasticity of Growing and Elastic Neural Networks in Online Continual Learning
Aug 2, 2026Jeong Min Kong, Richard S. SuttonLoss of Plasticity Dynamic Neural Networks
Department of Electrical and Computer Engineering University of California, Los Angeles (UCLA) · Department of Computing Science University of Alberta Alberta Machine Intelligence Institute (Amii)
DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments
Aug 1, 2026Yanming Lyu, Yue Cheng, Lingkun Li +4Intelligent Transportation Systems Online Continual Learning
Beijing Jiaotong University Beijing, China · Didichuxing Co. Ltd Beijing, China · Lancaster University Lancaster, United Kingdom
Versatile On-device Adaptation at the Edge by Unifying Few-shot, Zero-shot, Continual, and In-context Learning
Jul 31, 2026Douwe den Blanken, Martin Lefebvre, Charlotte FrenkelZero-Shot Learning On-Device Training
Microelectronics Department (EEMCS Faculty), Delft University of Technology, 2628 CD Delft, Netherlands
UniMem: Complementary Episodic-to-Parametric Memory for Boundary-Agnostic Task Streams
Jul 28, 2026Siyu Xia, Chenheng Zhang, Yanting Wu +8Continual Learning for LLM Agents Online Continual Learning
Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Artificial Intelligence, University of Chinese Academy of Sciences, China · State Key Lab of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University +3
GeoMFD: Continual Drone-View Geo-Localization with Geometry-Aware Adapter and Margin-Field Distillation
Jul 28, 2026Zhongwei Chen, Hai-jun Rong, Tao Zhang +4Cross-View Geo-Localization Online Continual Learning
School of Aerospace Engineering, Xi’an Jiaotong University · Institute of Automation, Chinese Academy of Sciences
A Continual Validation, Updating, and Decision-Making Framework for Self-Adaptive Digital Twins via Robust Model Predictive Control: A Case Study in Additive Manufacturing
Jul 20, 2026Yi-Ping Chen, Ying-Kuan Tsai, Vispi Karkaria +3Neural Surrogate Modeling Concept Drift
Department of Mechanical Engineering, Northwestern University · Department of Industrial Engineering and Management Science, Northwestern University
Learning to Fine-tune Foundation Models under Resource Limitations
Jul 12, 2026Thomas Tsouparopoulos, Iordanis KoutsopoulosFine-Tuning LLM Fine-Tuning
Department of Informatics Athens University of Economics and Business Athens, Greece
Interference and Retention in Continual Learning
Jul 10, 2026Julius StörkContinual Learning Online Continual Learning
VARTA Microbattery GmbH, Ellwangen, Germany
To Retain or to Adapt? Generalizing Continual Learning
Jul 6, 2026Giulia Lanzillotta, Mandana Samiei, Doina Precup +2Continual Learning Online Continual Learning
ETH AI Center, Department of Computer Science, ETH Zürich · Mila - Quebec AI Institute, School of Computer Science, McGill University · Mila - Quebec AI Institute +1
FlatManifold: Robust Continual Learning under Severe Label Noise and Domain Shifts via Intrinsic Manifold Flattening
Jul 6, 2026Rai Hisada, Kanji TanakaContinual Learning Domain-Incremental Learning
Department of Mechanical Engineering, Faculty of Engineering, University of Fukui, Fukui 910-8507, Japan

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Frozen Models, Evolving Expertise: Model-Agnostic Learning from Deployment Experience for Multimodal Medical AI

Yexiao He, Yucheng Tang, Pengfei Guo, Yufan He+5

University of Maryland, College Park · NVIDIA

Medical LLMs Continual Learning for VLMs Online Continual Learning Memory-Augmented VLMs Medical VLMs

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Large language models (LLMs) and vision-language models (VLMs) are usually frozen after deployment, so they do not learn from the cases they solve. This is especially concerning in medicine, where new clinical evidence, updated guidelines, and new therapies can change established practice. Fine-tuning can update the model, but it requires access to model weights and additional training. Parameter-free methods avoid training, but they may overfit a fixed validation set, lack reliable domain knowledge, or lose visual details by saving experience only as text. To address these limitations, we present a model-agnostic framework that allows frozen LLMs and VLMs to learn from deployment experience through three forms of external expertise: a Skill that guides reasoning and tool use, a Knowledge Memory that stores reliable facts supported by earlier cases or trusted external evidence, and a Multimodal Knowledge Base that keeps visual examples and guides the model to relate each retrieved case to the current image. Instead of relying on a fixed validation set, a validation strategy keeps an update only if it helps on new cases without degrading performance on earlier ones. Across six benchmarks covering clinical diagnosis, clinical workflows, medical reasoning, and medical and non-medical visual reasoning, and with four open-weight and closed-source base models, our framework improves performance during online deployment by up to 34.2% over the base model on medical tasks, generalizes to unseen cases, transfers to other models without further optimization, and works in non-medical domains.

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Latest papers 46