Transfer Learning

CVPR 2024arXiv:2403.03421

#2

LEAD: Learning Decomposition for Source-free Universal Domain Adaptation

Sanqing Qu, Tianpei Zou, Lianghua He et al.

43

AAAI 2024arXiv:2310.07730

#3

Domain-Controlled Prompt Learning

Qinglong Cao, Zhengqin Xu, Yuntian Chen et al.

prompt learningvision-language modelsdomain adaptationremote sensing images+3

30

CVPR 2024arXiv:2404.07155

#4

Unified Language-driven Zero-shot Domain Adaptation

Senqiao Yang, Zhuotao Tian, Li Jiang et al.

29

ECCV 2024arXiv:2407.05005

#5

Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching

Yichen Li, Wenchao Xu, Haozhao Wang et al.

federated learningdomain-incremental learningknowledge matchingpersonalized federated learning+4

28

CVPR 2024arXiv:2403.00567

#6

Flatten Long-Range Loss Landscapes for Cross-Domain Few-Shot Learning

Yixiong Zou, Yicong Liu, Yiman Hu et al.

22

AAAI 2025arXiv:2412.14528

#7

Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on Language Models

Xiao Cui, Mo Zhu, Yulei Qin et al.

22

AAAI 2024arXiv:2312.14990

#8

Learning to Prompt Knowledge Transfer for Open-World Continual Learning

Yujie Li, Xin Yang, Hao Wang et al.

continual learningopen-world learningknowledge transferprompt learning+4

22

CVPR 2024arXiv:2403.15760

#9

An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning

Jianqing Zhang, Yang Liu, Yang Hua et al.

20

CVPR 2024arXiv:2312.12478

#10

ProS: Prompting-to-simulate Generalized knowledge for Universal Cross-Domain Retrieval

Fang Kaipeng, Jingkuan Song, Lianli Gao et al.

19

ECCV 2024arXiv:2403.09296

#11

Select and Distill: Selective Dual-Teacher Knowledge Transfer for Continual Learning on Vision-Language Models

Yu-Chu Yu, Chi-Pin Huang, Jr-Jen Chen et al.

vision-language modelscontinual learningknowledge distillationcatastrophic forgetting+3

16

ICLR 2024arXiv:2310.11451

#12

Seeking Neural Nuggets: Knowledge Transfer in Large Language Models from a Parametric Perspective

Ming Zhong, Chenxin An, Weizhu Chen et al.

16

ICML 2025arXiv:2502.02017

#13

Multi-Domain Graph Foundation Models: Robust Knowledge Transfer via Topology Alignment

Shuo Wang, Bokui Wang, Zhixiang Shen et al.

15

AAAI 2025arXiv:2502.18510

#14

Multi-Teacher Knowledge Distillation with Reinforcement Learning for Visual Recognition

Chuanguang Yang, XinQiang Yu, Han Yang et al.

12

CVPR 2025arXiv:2411.14519

#15

Tra-MoE: Learning Trajectory Prediction Model from Multiple Domains for Adaptive Policy Conditioning

Jiange Yang, Haoyi Zhu, Yating Wang et al.

11

ECCV 2024arXiv:2407.13771

#16

Training-Free Model Merging for Multi-target Domain Adaptation

Wenyi Li, Huan-ang Gao, Mingju Gao et al.

model mergingmulti-target domain adaptationscene understandingnormalization layer statistics+4

11

AAAI 2024arXiv:2403.17374

#17

Symmetric Self-Paced Learning for Domain Generalization

Di Zhao, Yun Sing Koh, Gillian Dobbie et al.

Multi-Domain Recommendation to Attract Users via Domain Preference Modeling

Hyunjun Ju, SeongKu Kang, Dongha Lee et al.

multi-domain recommendationdomain preference modelingmasked domain modelingcross-domain knowledge transfer+2

9

AAAI 2024arXiv:2312.11260

#19

Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning

YongJin Yang, Taehyeon Kim, Se-Young Yun

cross-domain few-shot learningnormalization layer adaptersprogressive learningadaptive distillation+4

8

AAAI 2025arXiv:2404.13322

#20

MergeNet: Knowledge Migration Across Heterogeneous Models, Tasks, and Modalities

Kunxi Li, Tianyu Zhan, Kairui Fu et al.

8

ICML 2025arXiv:2503.04429

#21

On the Transfer of Object-Centric Representation Learning

Aniket Rajiv Didolkar, Andrii Zadaianchuk, Anirudh Goyal et al.

Mix-CPT: A Domain Adaptation Framework via Decoupling Knowledge Learning and Format Alignment

Jinhao Jiang, Junyi Li, Xin Zhao et al.

Activation Space Interventions Can Be Transferred Between Large Language Models

Narmeen Oozeer, Dhruv Nathawani, Nirmalendu Prakash et al.

6

vision-language modelscontinual learningcatastrophic forgettingzero-shot transfer+3

#24

Adapt without Forgetting: Distill Proximity from Dual Teachers in Vision-Language Models

MENGYU ZHENG, Yehui Tang, Zhiwei Hao et al.

ECCV 2024

6

CVPR 2025arXiv:2503.15404

#25

Improving Adversarial Transferability on Vision Transformers via Forward Propagation Refinement

Yuchen Ren, Zhengyu Zhao, Chenhao Lin et al.

5

AAAI 2025arXiv:2501.15052

#26

Graph-Based Cross-Domain Knowledge Distillation for Cross-Dataset Text-to-Image Person Retrieval

Bingjun Luo, Jinpeng Wang, Zewen Wang et al.

5

ICML 2025arXiv:2410.08194

#27

Features are fate: a theory of transfer learning in high-dimensional regression

Javan Tahir, Surya Ganguli, Grant Rotskoff

5

ICLR 2024arXiv:2403.07030

#28

AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation

Zihao Tang, Zheqi Lv, Shengyu Zhang et al.

ICLR 2024arXiv:2212.01168

#29

Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning

Yeongwoo Song, Hawoong Jeong

ICCV 2025arXiv:2503.08751

#30

Learning to Unlearn while Retaining: Combating Gradient Conflicts in Machine Unlearning

Gaurav Patel, Qiang Qiu

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning

Qi Wang, Zhipeng Zhang, Baao Xie et al.

AAAI 2024arXiv:2309.10302

#32

Decoupled Training: Return of Frustratingly Easy Multi-Domain Learning

Ximei Wang, Junwei Pan, Xingzhuo Guo et al.

multi-domain learningdataset biasdomain dominationdomain-specific towers+4

AAAI 2025arXiv:2509.04535

#33

Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model

Jincheng Zhong, XiangCheng Zhang, Jianmin Wang et al.

In-Context Policy Adaptation via Cross-Domain Skill Diffusion

Minjong Yoo, Woo Kyung Kim, Honguk Woo

3

AAAI 2025arXiv:2412.08979

#35

A Wander Through the Multimodal Landscape: Efficient Transfer Learning via Low-rank Sequence Multimodal Adapter

Zirun Guo, Xize Cheng, Yangyang Wu et al.

3

AAAI 2025arXiv:2412.15835

#36

Enhancing Generalized Few-Shot Semantic Segmentation via Effective Knowledge Transfer

Xinyue Chen, Miaojing Shi, Zijian Zhou et al.

3

ICCV 2025arXiv:2508.05689

#37

Selective Unlearning via Representation Erasure Using Domain Adversarial Training

Nazanin Sepahvand, Eleni Triantafillou, Hugo Larochelle et al.

Bridging Domain Generalization to Multimodal Domain Generalization via Unified Representations

Hai Huang, Yan Xia, Sashuai Zhou et al.

Boosting Adversarial Transferability via Residual Perturbation Attack

Jinjia Peng, Zeze Tao, Huibing Wang et al.

2

ICLR 2025arXiv:2504.09205

#40

What's in a Latent? Leveraging Diffusion Latent Space for Domain Generalization

Xavier Thomas, Deepti Ghadiyaram

Query-based Knowledge Transfer for Heterogeneous Learning Environments

Norah Alballa, Wenxuan Zhang, Ziquan Liu et al.

knowledge transferheterogeneous learning environmentsfederated learningdecentralized collaborative learning+4

2

CVPR 2024arXiv:2403.11234

#42

Unified Graph Neural Networks Pre-training for Multi-domain Graphs

Mingkai Lin, Xiaobin Hong, Wenzhong Li et al.

Universal Semi-Supervised Domain Adaptation by Mitigating Common-Class Bias

Wenyu Zhang, Qingmu Liu, Felix Ong et al.

2

ECCV 2024arXiv:2409.18565

#44

When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration

Quan Shi, Carlos Jimenez, Shunyu Yao et al.

Quantifying Cross-Modality Memorization in Vision-Language Models

Yuxin Wen, Yangsibo Huang, Tom Goldstein et al.

Generalizable Domain Adaptation for Sim-and-Real Policy Co-Training

Shuo Cheng, Liqian Ma, Zhenyang Chen et al.

Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphs

Kai Wang, Siqiang Luo, Caihua Shan et al.

Harmonizing knowledge Transfer in Neural Network with Unified Distillation

yaomin huang, faming Fang, Zaoming Yan et al.

knowledge distillationfeature aggregationunified distillation frameworkintermediate layer features+3

AAAI 2024arXiv:2402.05942

#49

Cooperative Knowledge Distillation: A Learner Agnostic Approach

Michael Livanos, Ian Davidson, Stephen Wong

knowledge distillationcounterfactual instance generationmulti-model cooperationtransfer learning+4

AAAI 2025arXiv:2412.13525

#50

Hybrid Data-Free Knowledge Distillation

Jialiang Tang, Shuo Chen, Chen Gong

AAAI 2025arXiv:2412.11788

#51

Knowledge-Guided Domain Adaptation Model for Transferring Drug Response Prediction from Cell Lines to Patients

Xuan Liu, Menglu Li

Neural Collapse Inspired Knowledge Distillation

Shuoxi Zhang, Zijian Song, Kun He

ICML 2025arXiv:2501.18836

#53

GraphKeeper: Graph Domain-Incremental Learning via Knowledge Disentanglement and Preservation

Zihao Guo, Qingyun Sun, Ziwei Zhang et al.

Link-based Contrastive Learning for One-Shot Unsupervised Domain Adaptation

Yue Zhang, Mingyue Bin, Yuyang Zhang et al.

Forget More to Learn More: Domain-specific Feature Unlearning for Semi-supervised and Unsupervised Domain Adaptation

Hritam Basak, Zhaozheng Yin

Transfer Learning for Nonparametric Contextual Dynamic Pricing

Fan Wang, Feiyu Jiang, Zifeng Zhao et al.

CVPR 2024arXiv:2404.01727

#57

ReSimAD: Zero-Shot 3D Domain Transfer for Autonomous Driving with Source Reconstruction and Target Simulation

Bo Zhang, Xinyu Cai, Jiakang Yuan et al.

Generalizing 6-DoF Grasp Detection via Domain Prior Knowledge

Haoxiang Ma, Modi Shi, Boyang GAO et al.

ICLR 2024arXiv:2302.02609

#59

Improving Domain Generalization with Domain Relations

Huaxiu Yao, Xinyu Yang, Xinyi Pan et al.

ICML 2025arXiv:2502.01804

#60

Model Inversion Robustness: Can Transfer Learning Help?

Sy-Tuyen Ho, Koh Jun Hao, Keshigeyan Chandrasegaran et al.

Transfer Q-Learning with Composite MDP Structures

Jinhang Chai, Elynn Chen, Lin Yang

ExPLoRA: Parameter-Efficient Extended Pre-Training to Adapt Vision Transformers under Domain Shifts

Samar Khanna, Medhanie Irgau, David Lobell et al.

Knowledge Swapping via Learning and Unlearning

Mingyu Xing, Lechao Cheng, Shengeng Tang et al.

Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging

Pierre Ablin, Angelos Katharopoulos, Skyler Seto et al.

#65

Domain-wise Data Acquisition to Improve Performance under Distribution Shift

Yue He, Dongbai Li, Pengfei Tian et al.

domain adaptationdistribution shiftdata acquisitioncross-distribution generalization+3

#66

A General Representation-Based Approach to Multi-Source Domain Adaptation

Ignavier Ng, Yan Li, Zijian Li et al.

Do Multiple Instance Learning Models Transfer?

Daniel Shao, Richard Chen, Andrew Song et al.

Tell, Don't Show: Language Guidance Eases Transfer Across Domains in Images and Videos

Tarun Kalluri, Bodhisattwa Prasad Majumder, Manmohan Chandraker

domain adaptationlanguage guidancecross-modal transferunsupervised adaptation+2

#69

Let Go of Your Labels with Unsupervised Transfer

Artyom Gadetsky, Yulun Jiang, Maria Brbic

unsupervised transferzero-shot transferfoundation modelsvision-language models+3

ICLR 2024arXiv:2305.14122

#70

Towards the Fundamental Limits of Knowledge Transfer over Finite Domains

Qingyue Zhao, Banghua Zhu

Transferring Learning Trajectories of Neural Networks

Daiki Chijiwa

CVPR 2024arXiv:2403.11674

#72

How Much Can Transfer? BRIDGE: Bounded Multi-Domain Graph Foundation Model with Generalization Guarantees

Haonan Yuan, Qingyun Sun, Junhua Shi et al.

Evaluating Transferability in Retrieval Tasks: An Approach Using MMD and Kernel Methods

Mengyu Dai, Amir Hossein Raffiee, Aashish Jain et al.

Towards Generalizing to Unseen Domains with Few Labels

Chamuditha Jayanga Galappaththige, Sanoojan Baliah, Malitha Gunawardhana et al.

ICML 2025arXiv:2505.24844

#75

Chameleon: A Flexible Data-mixing Framework for Language Model Pretraining and Finetuning

Wanyun Xie, Francesco Tonin, Volkan Cevher

ICML 2025arXiv:2505.16080

#76

Boosting Multi-Domain Fine-Tuning of Large Language Models through Evolving Interactions between Samples

Xize Liang, Lin Yang, Jie Wang et al.

C2KD: Bridging the Modality Gap for Cross-Modal Knowledge Distillation

Fushuo Huo, Wenchao Xu, Jingcai Guo et al.

SynEVO: A neuro-inspired spatiotemporal evolutional framework for cross-domain adaptation

jiayue Liu, Zhongchao Yi, Zhengyang Zhou et al.

ICML 2024arXiv:2206.04277

#79

On Hypothesis Transfer Learning of Functional Linear Models

Haotian Lin, Matthew Reimherr

transfer learningfunctional linear regressionreproducing kernel hilbert spacehypothesis transfer learning+2

ICML 2025arXiv:2506.02843

#80

Random Registers for Cross-Domain Few-Shot Learning

Shuai Yi, Yixiong Zou, Yuhua Li et al.

ICLR 2024arXiv:2310.17653

#81

Your Transferability Barrier is Fragile: Free-Lunch for Transferring the Non-Transferable Learning

Ziming Hong, Li Shen, Tongliang Liu

Enhancing Foundation Models with Federated Domain Knowledge Infusion

Jiaqi Wang, Jingtao Li, Weiming Zhuang et al.

Pessimism Principle Can Be Effective: Towards a Framework for Zero-Shot Transfer Reinforcement Learning

Chi Zhang, Ziying Jia, George Atia et al.

Mutual Learning for SAM Adaptation: A Dual Collaborative Network Framework for Source-Free Domain Transfer

Yabo Liu, Waikeung Wong, Chengliang Liu et al.

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model

Karsten Roth, Lukas Thede, A. Sophia Koepke et al.

ICLR 2024arXiv:2405.02797

#86

Adapting to Distribution Shift by Visual Domain Prompt Generation

Zhixiang Chi, Li Gu, Tao Zhong et al.

#87

Parameter Efficient Self-Supervised Geospatial Domain Adaptation

Linus Scheibenreif, Michael Mommert, Damian Borth

Gradual Divergence for Seamless Adaptation: A Novel Domain Incremental Learning Method

Jeeveswaran Kishaan, Elahe Arani, Bahram Zonooz

domain incremental learningcatastrophic forgettingrepresentation driftfeature space adaptation+2

AAAI 2025arXiv:2412.16502

#89

Learning to Transform Dynamically for Better Adversarial Transferability

Rongyi Zhu, Zeliang Zhang, Susan Liang et al.

MDFL: Multi-Domain Diffusion-Driven Feature Learning

Daixun Li, Weiying Xie, Jiaqing Zhang et al.

See Through Their Minds: Learning Transferable Brain Decoding Models from Cross-Subject fMRI

Yulong Liu, Yongqiang Ma, Guibo Zhu et al.

Harnessing Language Model for Cross-Heterogeneity Graph Knowledge Transfer

Jinyu Yang, Ruijia Wang, Cheng Yang et al.

Multi-Domain Deep Learning from a Multi-View Perspective for Cross-Border E-commerce Search

Low Category Uncertainty and High Training Potential Instance Learning for Unsupervised Domain Adaptation

Xinyu Zhang, Meng Kang, Shuai Lü

Graph Disentangled Contrastive Learning with Personalized Transfer for Cross-Domain Recommendation

SemTra: A Semantic Skill Translator for Cross-Domain Zero-Shot Policy Adaptation

Sangwoo Shin, Minjong Yoo, Jeongwoo Lee et al.

Spatial-Temporal Knowledge Distillation for Takeaway Recommendation

Shuyuan Zhao, Wei Chen, Boyan Shi et al.

#98

Repurposing Ensemble of Black-Box Models to New Task Domains

Minh Hoang, Nghia Hoang

Multi-Source Collaborative Gradient Discrepancy Minimization for Federated Domain Generalization

Yikang Wei, Yahong Han

Contextual Structure Knowledge Transfer for Graph Neural Networks

Zhiyuan Yu, Wenzhong Li, Zhangyue Yin et al.

AAAI 2025