Cross-Domain Transfer Learning

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Beyond Feature and Structure Alignment: Learning Transferable Propagation Knowledge for Graph Foundation Models
Jul 31, 2026Yi Wang, Jitao Zhao, Di Jin +1Message Passing Neural Networks Cross-Domain Generalization
Tianjin University Tianjin, China
PerturbMap: Cross-Context Transfer of Single-Cell Perturbation Responses
Jul 30, 2026Panpan Cui, Yiqi Liu, Wenhao SunSingle-Cell Perturbation Modeling Cross-Domain Transfer Learning
School of Advanced Interdisciplinary Sciences, University of Chinese Academy of Sciences · Institute of Computing Technology, CAS; University of Chinese Academy of Sciences · 3Hong Kong University of Science and Technology
What Makes Graph Unified? Principles and Generative Sliding-Window Transformer for Graph Foundation Models
Jul 30, 2026Dongxiao He, Siqi Liu, Jitao Zhao +3Cross-Domain Transfer Learning Graph Foundation Models
School of Computer Science and Technology Tianjin University Tianjin, China · School of Economics and Management Beijing University of Posts and Telecommunications Beijing, China
A Lightweight Foundation Model for Collider Physics with Multi-Domain Adaptation
Jul 29, 2026Liangyu Wu, Qibin Liu, Alexander Yue +1Self-Supervised Pre-Training High-Energy Physics
Department of Physics, Stanford University, 450 Jane Stanford Way, Stanford, 94305, CA, USA. · SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, 94025, CA, USA.
Sharpness-aware Model Merging with Salience Recovery for LLM-based Cross-Domain Sequential Recommendation
Jul 28, 2026Huwei Ji, Jiajie Su, Yuyuan Li +2Sequential Recommendation Cross-Domain Transfer Learning
Zhejiang University Hangzhou, China · Hangzhou Dianzi University Hangzhou, China
CD-RMOT-Bench: Benchmarking the Cross-Domain Referring Multi-Object Tracking
Jul 28, 2026Xiangqun Zhang, Likai Wang, Zekun Qian +2Synthetic-to-Real Domain Adaptation Cross-Domain Transfer Learning
School of Computer Science and Technology, Tianjin University, Tianjin, China · Faculty of Computer Science and Artificial Intelligence, Shenzhen University of Advanced Technology, Shenzhen, China
Multi-Task Learning for Heterogeneous Prediction from Video Game State with Transfer Learning
Jul 23, 2026Jonas Peché, Aliaksei Tsishurou, Alexander Zap +1Multi-Task Learning Cross-Domain Transfer Learning
Computer Graphics Johannes Kepler University Linz Linz, Austria · Independent Researcher Wroclaw, Poland · DS Research Wargaming Berlin, Germany
AUCH-Net: Action Unit-Based Consistency-Aware Hypergraph Network for Cross-Domain Few-Shot Facial Expression Recognition
Jul 23, 2026Xinhan Qiu, Yan Yan, Rui Zhu +2Few-Shot Learning Cross-Domain Transfer Learning
Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, School of Informatics, Xiamen University, Xiamen 361102, China · Fujian Key Laboratory of Pattern Recognition and Image Understanding, Xiamen University of Technology, Xiamen 361024, China · Bayes Business School, City St George’s, University of London, London, EC1Y 8TZ, UK +1
Multi-stage Dynamic Selection for Cross-Project Defect Prediction
Jul 22, 2026Juscimara G. Avelino, Juscelino S. A. Junior, George D. C. Cavalcanti +1Ensemble Learning Cross-Domain Transfer Learning
Centro de Inform´atica, Universidade Federal de Pernambuco, Recife, Brazil · ´Ecole de Technologie Sup´erieure, University of Quebec, Montreal, Canada
Domain-Adapted Power Curve for Cross-Farm Applications
Jul 22, 2026Ahmadreza Chokhachian, V. Roshan Joseph, Yu DingDomain Adaptation Cross-Domain Transfer Learning
H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology
Unveiling Invariant and Transferable Latent Factors Across Heterogeneous Environments via ATLAS
Jul 20, 2026Yihong Gu, Katherine Liao, Tianxi CaiLatent Variable Models Domain Generalization
Harvard University
What Transfers Under Source Shift? Definitions, Examples, and Fine-Tuning for Climate Disclosure Classification
Jul 20, 2026Guosheng Li, Fenghui Ren, Bin Liu +5LLM Fine-Tuning Few-Shot Prompting
School of Computing and Information Technology, University of Wollongong · School of Business, University of Wollongong · Business School, University of Sydney +1
SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems
Jul 14, 2026Yuxuan Ren, Fan Yang, Jianhua Yao +1Autoencoders 3D Molecular Generation
Department of Computer Science National University of Singapore · Tencent AI for Life Science Lab
Co-Adaptive Multi-Task LoRA: Transfer-Aware, Label-Free Control of Domain Participation
Jul 3, 2026Wei Zhang, Lin Tang, Ming Zhao +1Multi-Task Learning Data Selection
1Sichuan University, Chengdu, China · University of Electronic Science and Technology of China, Chengdu, China
Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion
Jul 3, 2026Jiawei Sheng, Taoyu Su, Xixun Lin +2Diffusion Model Guidance KG Embedding
Institute of Information Engineering, Chinese Academy of Sciences Beijing, China · Institute of Information Engineering, Chinese Academy of Sciences School of Cyber Security, UCAS Beijing, China
Meta-Transfer Learning for mmWave Beam Alignment
Jul 1, 2026Ahmet Nuri Cevik, Sinem ColeriMeta-Learning Wireless Communications
Device Passport: Enabling Spatio-Temporal Pretrained Models to Generalize Across Input Layouts
Jun 30, 2026Geeling Chau, Ran Liu, Juri Minxha +5Representation Learning Cross-Domain Transfer Learning
California Institute of Technology, Pasadena, CA, USA · Apple, Cupertino, CA, USA
Distributed Hierarchical Temporal Memory with Shared Associative Memory for Cross-Entity Preemptive Warning
Jun 30, 2026Pavia Bera, Jennifer Adorno, Sanjukta BhanjaOnline Anomaly Detection Cross-Domain Transfer Learning
University of South Florida, Tampa, FL, USA
Additive Causal Construction for Transferable and Reconfigurable Cross-System Learning in Multi-Source Image Fusion
Jun 30, 2026Zhizhong Fu, Wei Zhou, Zhaoyang Jiang +5Multi-Source Image Fusion Causal Representation Learning
School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital, Huzhou 313000, China. · Department of Radiology, Huzhou Maternity & Child Health Care Hospital Affiliated to Huzhou Normal University,Huzhou 313000,China. +3
Heterogeneous Tactile Transformer
Jun 29, 2026Jianxin Bi, Qiang Wang, Jayaram Reddy +4Representation Learning Multimodal Pretraining
National University of Singapore · Carnegie Mellon University · 3Smart Systems Institute, NUS
Two-Stage Cross-Domain Cervical Abnormality Screening with Cytopathological Image Synthesis and Knowledge Distillation
Jun 26, 2026Jincheng Li, Yuzhi He, Yihui Zhan +6Computational Pathology Cross-Domain Transfer Learning
School of Artificial Intelligence and Computer Science, Nantong University, Nantong 226019, China · School of Telecommunications Engineering, Xidian University, Xi’an 710126, China · College of Computer Science and Technology, Zhejiang University, Hangzhou 310058, China +2
Beyond Single-Source Cognitive Taskonomy:Multi-Source Task Relations through fMRI Transfer Learning
Jun 24, 2026Junfeng Xia, Wendu Li, Mengjiao Zhang +1Task Transferability Estimation Cross-Domain Transfer Learning
Department of Biomedical Engineering, Southern University of Science and Technology Shenzhen, China
Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR
Jun 23, 2026Yongjin Yang, Jiarui Liu, Yinghui He +3RL for Language Model Reasoning Curriculum RL
Jinesis Lab, University of Toronto & Vector Institute1 · Carnegie Mellon University2 · Princeton University3 +4
The Geometry of Sequential Learning: Lie-Bracket Prediction of Transfer Order
Jun 23, 2026John SweeneyPairwise Ranking Cross-Domain Transfer Learning
Sideplane AI
ASALT: Adaptive State Alignment for Lateral Transfer in Multi-agent Reinforcement Learning
Jun 23, 2026Anurag Akula, Satheesh K. Perepu, Abhishek Sarkar +1Cross-Domain Transfer Learning State Representation Learning
Indian Institute of Technology Madras, India · Ericsson Research, India
An LLM-based Two-Stage Transformer Framework for Cross-Domain Bearing Fault Diagnosis with Limited Data
Jun 23, 2026Jinghan Wang, Feng Cheng, Wentao Wu +3Few-Shot Domain Adaptation Predictive Maintenance
School of Mechatronics Engineering, Harbin Institute of Technology, Harbin 150001, China
Training-free Cross-domain Few-shot Segmentation via Robust Semantic Representation and Matching
Jun 23, 2026Sujun Sun, Mingwu Ren, Haofeng ZhangFew-Shot Learning Cross-Domain Transfer Learning
School of Computer Science and Engineering, Nanjing University of Science and Technology, China · State Key Laboratory of Intelligent Manufacturing of Advanced Construction Machinery, China
Handling Feature Heterogeneity with Learnable Graph Patches
Jun 16, 2026Yifei Sun, Yang Yang, Xiao Feng +4Graph Representation Learning Cross-Domain Transfer Learning
Zhejiang University Hangzhou, China · Huazhong University of Science and Technology Wuhan, China · Finvolution Group Shanghai, China
Beyond Domains: Reusing Web Skills via Transferable Interaction Patterns
Jun 16, 2026Shiqi He, Yue Cui, Feijie Wu +5Tool-Augmented Language Model Agents LLM Agent Skill Learning
University of Michigan · Alibaba Group · Purdue University +2
Transfer Learning Across Policy Regimes in Adaptive Multi-Agent Systems
Jun 15, 2026Roberto GarroneCross-Domain Transfer Learning Transfer Learning
Open University of Cyprus

Jul 31, 2026, cs.LGJ/K move · Enter open · S save

Beyond Feature and Structure Alignment: Learning Transferable Propagation Knowledge for Graph Foundation Models

Yi Wang, Jitao Zhao, Di Jin, Dongxiao He

Tianjin University Tianjin, China

Message Passing Neural Networks Cross-Domain Generalization Cross-Domain Transfer Learning Graph Foundation Models

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Graph Foundation Models (GFMs) have recently emerged as a promising paradigm for enabling knowledge transfer across diverse domains. Unlike traditional graph learning methods that are typically designed for in-domain settings, GFMs aim to learn transferable knowledge that can generalize to unseen graph domains. However, unlike language or visual data, graphs lack intrinsic and unified representation units, such as tokens in language and patches in vision, making it challenging to identify transferable knowledge units for building graph foundation models. Existing graph foundation models mainly focus on mitigating domain discrepancies through feature alignment and structure alignment, while overlooking the exploration of transferable knowledge units underlying graph data. Moreover, these methods generally rely on fixed propagation mechanisms during message passing, overlooking the heterogeneity in propagation patterns, as different edges may exhibit distinct propagation patterns for different feature dimensions. To address these limitations, we propose a Propagation-aware Graph Foundation Model (ProGFM), which regards the propagation relationships between edges and feature dimensions as transferable knowledge units. Through a propagation relationship prototype bank, ProGFM learns cross-domain transferable propagation knowledge, enabling adaptive information aggregation in unseen graph domains. Extensive experiments across various cross-domain transfer scenarios demonstrate that ProGFM possesses strong cross-domain knowledge transfer capability and exhibits superior generalization performance compared with existing methods.

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