Transfer Learning

Ask about this topic

Overview

Transfer learning asks how a model trained on one task or domain can help with another, reducing the need for target-specific data and computation. Common approaches include pretraining followed by fine-tuning or parameter-efficient adapters, feature alignment for domain shifts, and knowledge transfer through distillation, model merging, or shared representations. Evaluations span zero-shot and few-shot transfer, cross-domain benchmarks in vision and language, and adaptation in settings such as clinical data, robotics, and scientific modeling. A central tension is that transferred knowledge can improve accuracy and sample efficiency or cause negative transfer; predicting when it will help, and separating reusable knowledge from dataset or architecture effects, remains difficult.

Latest papers

CardsList

422 papers62 papers in the last four weeks, up 29% on the four weeks before. 0.4% of all new papers.

  1. Annotations Are Not All You Need: A Cross-modal Knowledge Transfer Network for Unsupervised Temporal Sentence Grounding

    May 29, 2026Xiang Fang, Daizong Liu, Wanlong Fang +4Temporal Video GroundingCross-Modal Representation Transfer

    Hubei Key Laboratory of Distributed System Security, Hubei Engineering Research Center on Big Data Security, School of Cyber Science and Engineering, Huazhong University of Science and Technology · Peking University · Henan University +3

  2. Learning Transferable Predictability Representations

    May 28, 2026Diyali Goswami, Auroop R. GangulyDynamical SystemsOrdinal Regression

    Sustainability and Data Sciences Laboratory (SDS Lab), Northeastern University, Boston, MA, USA · AI4CaS: AI for Climate and Sustainability, Institute for Experiential AI, Northeastern University, Boston, MA, USA · Pacific Northwest National Laboratory (PNNL), Richland, WA, USA

  3. LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation

    May 28, 2026Hua Zheng, Shali Jiang, Boyang Liu +44Transfer LearningRecommender Systems

  4. Bilinear Coordinate Alignment for Training-Free Task-Vector Transfer

    May 27, 2026Jungyong Son, Jinwook Jung, Minhee Park +1Orthogonal Procrustes AlignmentTask Vectors

    Dept. of Artificial Intelligence, 2 Dept. of Data Science Hanyang University

  5. Transfer learning RGB models to hyperspectral images with trainable tensor decompositions

    May 27, 2026Mariette Schönfeld, Laurens Devos, Wannes Meert +1Tensor DecompositionHyperspectral Imaging

    KU Leuven, Dept. of Computer Science, B-3000 Leuven, Belgium · Leuven.AI - KU Leuven Institute for AI, B-3000 Leuven, Belgium

  6. Adapting Automotive Aerodynamics Surrogates to New Vehicle Families via Transfer Learning

    May 27, 2026Seunghwan Keum, Alok WareyAutomotive AerodynamicsPDE Surrogate Modeling

    General Motors Research and Development

  7. Leveraging pretrained RGB denoisers for hyperspectral image restoration

    May 23, 2026Daniele Picone, Mohamad Jouni, Mauro Dalla-MuraHyperspectral ImagingTransfer Learning

    Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-Lab, 38000, Grenoble, France

  8. Plume Segmentation from MethaneSAT with Cross-Sensor Transfer Learning and Physics-Informed Postprocessing

    May 22, 2026Manuel Pérez-Carrasco, Maya Nasr, Zhan Zhang +16Remote Sensing Image SegmentationInstance Segmentation

    Center for Astrophysics | Harvard & Smithsonian, Cambridge, MA · Environmental Defense Fund, Washington, D.C., USA · Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA, USA +7

  9. Distributionally Robust Transfer Learning with Structurally Missing Covariates, with Application to Cross-National Cardiac Arrest Prediction

    May 22, 2026Siqi Li, Chuan Hong, Ziye Tian +9HealthcareClinical Outcome Prediction

    Centre for Biomedical Data Science, Duke-NUS Medical School, Singapore · 2Duke-NUS AI + Medical Sciences Initiative, Duke-NUS Medical School, Singapore · Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA +13

  10. LWM-CDE: A Representation Space for Wireless Data Reasoning and Transferability

    May 22, 2026Sadjad Alikhani, Akshay Malhotra, Shahab Hamidi-Rad +1Contrastive LearningRepresentational Similarity Analysis

    School of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85281 USA · InterDigital, Inc., USA

  11. Rethinking Transfer Learning for Industrial Inspection: DINOv3 vs. ImageNet Pretraining Across RGB and X-ray Tasks

    May 22, 2026Mehdi Gharbage, Céline Teulière, Pierre Bouges +1Self-Supervised Pre-TrainingIndustrial Anomaly Detection

    1Michelin Tyres Manufacturer · 2Universit´e Clermont Auvergne, CNRS, Institut Pascal, Clermont-Ferrand, France

  12. Uncovering the Latent Potential of Deep Intermediate Representations

    May 21, 2026Arnesh Batra, Arush Gumber, Aniket Khandelwal +2Neural Representation GeometryHierarchical Representation Learning

    SBILab, Indraprastha Institute of Information Technology Delhi, Delhi, India.

  13. RADAR: Relative Angular Divergence Across Representations

    May 21, 2026Xavier Cadet, Mateusz Nowak, Peter ChinRepresentation GeometryTask Transferability Estimation

    Dartmouth College

  14. Evolutionary Multi-Task Optimization for LLM-Guided Program Discovery

    May 21, 2026Halil Alperen Gozeten, Xuechen Zhang, Emrullah Ildiz +3Evolutionary OptimizationEvolutionary Multitask Optimization

    University of Michigan - Ann Arbor · University of California San Diego

  15. TriForces: Augmenting Atomistic GNNs for Transferable Representations

    May 20, 2026Ali Ramlaoui, Alexandre Duval, Hannah Bull +4Disentangled Representation LearningMachine Learning Interatomic Potentials

    Entalpic, Paris, France · Universit´e Paris-Saclay, CentraleSup´elec, Inria, Gif-sur-Yvette, France

  16. Sample Complexity of Transfer Learning: An Optimal Transport Approach

    May 19, 2026Haoyang Cao, Xin Guo, Wenpin Tang +1Sample ComplexityTransfer Learning

    Department of Applied Mathematics and Statistics, John Hopkins University, Baltimore, MD, USA · Department of Industrial Engineering and Operations Research, University of California, Berkeley, CA, USA · Department of Industrial Engineering and Operations Research, Columbia University, New York, NY, USA +1

  17. Oracle Supervision Transfers for Hyperparameter Prediction in Model-Based Image Denoising

    May 19, 2026Jianmin Liao, Lixin Shen, Yuesheng XuHyperparameter TransferTransfer Learning

    Department of Mathematics Syracuse University · Department of Mathematics & Statistics Old Dominion University

  18. LLM Pretraining Shapes a Generalizable Manifold: Insights into Cross-Modal Transfer to Time Series

    May 19, 2026Alexis Roger, Prateek Humane, Zhenghan Tai +4Cross-Modal LearningLanguage Model Pretraining

    Université de Montréal Mila - Quebec AI Institute

  19. When Does Self-Supervised Learning Transfer to Time-Series Tasks?

    May 19, 2026Noam Major, Kathy Razmadze, Yoli ShavitSelf-Supervised Pre-TrainingTime Series Classification

    Faculty of Engineering, Bar-Ilan University, Israel

  20. PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels

    May 19, 2026Berkay Guler, Giovanni Geraci, Hamid JafarkhaniRepresentation LearningMasked Autoencoders

    Center for Pervasive Communications and Computing, University of California, Irvine CA, USA · Nokia and Universitat Pompeu Fabra, Spain

  21. Fine-tuning language encoding models on slow fMRI improves prediction for fast ECoG

    May 19, 2026Aditya R. Vaidya, Richard J. Antonello, Alexander G. HuthCross-Modal LearningFunctional Magnetic Resonance Imaging

    Department of Computer Science The University of Texas at Austin, USA · Zuckerman Mind Brain Behavior Institute Columbia University, USA · Departments of Neuroscience and Statistics University of California, Berkeley, USA

  22. Benchmarking transferability of SSL pretraining to same and different modality segmentation tasks

    May 18, 2026Jue Jiang, Harini VeeraraghavanCross-Modality Medical Image SegmentationSelf-Supervised Pre-Training

    Department of Medical Physics, Memorial Sloan Kettering Cancer Center

  23. Transfer Learning for Customized Car Racing Environments

    May 18, 2026Benedict Florance Arockiaraj, Richard Chang, Wesley YeeAutonomous RacingCross-Domain Transfer Learning

    SEAS

  24. Cross-Subject Intracranial EEG Reconstruction from Scalp Recordings Using Multi-Scale Cross-Attention Transformers

    May 17, 2026Tien-Dat Pham, Xuan-The TranCross-Subject EEG DecodingElectroencephalography

    HAI-Smartlink Research Lab, Anchi STE Company, Haiphong, Vietnam · School of Mechanical Engineering, Vietnam Maritime University, Haiphong, Vietnam

  25. VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment

    May 16, 2026Amy Makawana, Abhijeet Parida, Marius George Linguraru +23D ViTsSelf-Supervised Pre-Training

    Institute of Health Informatics, University College London, London, UK · Sheikh Zayed Institute for Pediatric Surgical Innovation, Children’s National Hospital, Washington, DC USA · School of Medicine and Health Sciences, George Washington University, Washington, DC, USA

  26. On the Limits of Latent Reuse in Diffusion Models

    May 13, 2026Yifeng Yu, Lu YuLatent Diffusion ModelsDomain Adaptation

    Department of Mathematical Sciences, Tsinghua University · Department of Data Science, City University of Hong Kong

  27. Leveraging Speech to Identify Signatures of Insight and Transfer in Problem Solving

    May 13, 2026Linas Nasvytis, Judith E. FanTransfer Learning

    Department of Psychology, Stanford University · Graduate School of Education, Stanford University · Department of Computer Science, Stanford University

  28. From Index to Equity: Pre-Training Transformers for Stock Return Prediction

    May 12, 2026Marie Soehl Coolsaet, Roberto Gallardo, Zhen GaoTime Series ForecastingTransfer Learning

    Faculty of Engineering, McMaster University · Department* of Economics, Universidad Veracruzana, Mexico

  29. A Transfer Learning Evaluation of Deep Neural Networks for Image Classification

    May 12, 2026Nermeen Abou Baker, Nico Zengeler, Uwe HandmannFine-TuningCross-Domain Transfer Learning

    Computer Science Institute, Ruhr West University of Applied Sciences, 46236 Bottrop, Germany

  30. Learning Subspace-Preserving Sparse Attention Graphs from Heterogeneous Multiview Data

    May 12, 2026Jie Chen, Yuanbiao Gou, Chuanbin Liu +2Graph Structure LearningMulti-View Learning

    College of Computer Science Sichuan University Chengdu, China · School of Economics and Management China University of Petroleum (Beijing) Beijing, China · Law School Sichuan University Chengdu, China +1