Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Weixin, Zhao, Yuhan, Chen, Li, Pan, Weike |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
by: Zhao, Yuhan, et al.
Published: (2026)
by: Zhao, Yuhan, et al.
Published: (2026)
Causality-Inspired Fair Representation Learning for Multimodal Recommendation
by: Chen, Weixin, et al.
Published: (2023)
by: Chen, Weixin, et al.
Published: (2023)
Privacy-Preserving Cross-Domain Sequential Recommendation
by: Lin, Zhaohao, et al.
Published: (2024)
by: Lin, Zhaohao, et al.
Published: (2024)
A Survey on Cross-Domain Sequential Recommendation
by: Chen, Shu, et al.
Published: (2024)
by: Chen, Shu, et al.
Published: (2024)
Leave No One Behind: Enhancing Diversity While Maintaining Accuracy in Social Recommendation
by: Li, Lei, et al.
Published: (2025)
by: Li, Lei, et al.
Published: (2025)
Post-Training Fairness Control: A Single-Train Framework for Dynamic Fairness in Recommendation
by: Chen, Weixin, et al.
Published: (2026)
by: Chen, Weixin, et al.
Published: (2026)
Joint Similarity Item Exploration and Overlapped User Guidance for Multi-Modal Cross-Domain Recommendation
by: Liu, Weiming, et al.
Published: (2025)
by: Liu, Weiming, et al.
Published: (2025)
Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation
by: Liu, Yu, et al.
Published: (2025)
by: Liu, Yu, et al.
Published: (2025)
BMLP: Behavior-aware MLP for Heterogeneous Sequential Recommendation
by: Li, Weixin, et al.
Published: (2024)
by: Li, Weixin, et al.
Published: (2024)
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation
by: Wei, Shaowei, et al.
Published: (2024)
by: Wei, Shaowei, et al.
Published: (2024)
A Survey on Multi-Behavior Sequential Recommendation
by: Chen, Xiaoqing, et al.
Published: (2023)
by: Chen, Xiaoqing, et al.
Published: (2023)
Sharpness-Aware Cross-Domain Recommendation to Cold-Start Users
by: Zeng, Guohang, et al.
Published: (2024)
by: Zeng, Guohang, et al.
Published: (2024)
Modeling User Preferences as Distributions for Optimal Transport-Based Cross-Domain Recommendation under Non-Overlapping Settings
by: Xiao, Ziyin, et al.
Published: (2025)
by: Xiao, Ziyin, et al.
Published: (2025)
KGBridge: Knowledge-Guided Prompt Learning for Non-overlapping Cross-Domain Recommendation
by: Wang, Yuhan, et al.
Published: (2025)
by: Wang, Yuhan, et al.
Published: (2025)
Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
by: Kang, Li, et al.
Published: (2025)
by: Kang, Li, et al.
Published: (2025)
Reproducibility Companion Paper:In-processing User Constrained Dominant Sets for User-Oriented Fairness in Recommender Systems
by: Liu, Yixiu, et al.
Published: (2025)
by: Liu, Yixiu, et al.
Published: (2025)
Matryoshka Representation Learning for Recommendation
by: Lai, Riwei, et al.
Published: (2024)
by: Lai, Riwei, et al.
Published: (2024)
Self-Supervised Representation Learning with ID-Content Modality Alignment for Sequential Recommendation
by: Zhou, Donglin, et al.
Published: (2025)
by: Zhou, Donglin, et al.
Published: (2025)
Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
by: Li, Xiaodong, et al.
Published: (2026)
by: Li, Xiaodong, et al.
Published: (2026)
MemRec: Collaborative Memory-Augmented Agentic Recommender System
by: Chen, Weixin, et al.
Published: (2026)
by: Chen, Weixin, et al.
Published: (2026)
Towards Multi-Behavior Multi-Task Recommendation via Behavior-informed Graph Embedding Learning
by: Lai, Wenhao, et al.
Published: (2026)
by: Lai, Wenhao, et al.
Published: (2026)
A Survey on Sequential Recommendation
by: Pan, Liwei, et al.
Published: (2024)
by: Pan, Liwei, et al.
Published: (2024)
SAGER: Self-Evolving User Policy Skills for Recommendation Agent
by: Tao, Zhen, et al.
Published: (2026)
by: Tao, Zhen, et al.
Published: (2026)
Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation
by: Wang, Li, et al.
Published: (2024)
by: Wang, Li, et al.
Published: (2024)
Enhancing Transferability and Consistency in Cross-Domain Recommendations via Supervised Disentanglement
by: Wang, Yuhan, et al.
Published: (2025)
by: Wang, Yuhan, et al.
Published: (2025)
Sample Enrichment via Temporary Operations on Subsequences for Sequential Recommendation
by: Chen, Shu, et al.
Published: (2024)
by: Chen, Shu, et al.
Published: (2024)
Lossless and Privacy-Preserving Graph Convolution Network for Federated Item Recommendation
by: Wu, Guowei, et al.
Published: (2024)
by: Wu, Guowei, et al.
Published: (2024)
Leveraging Multimodal Data and Side Users for Diffusion Cross-Domain Recommendation
by: Zhang, Fan, et al.
Published: (2025)
by: Zhang, Fan, et al.
Published: (2025)
Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference
by: Du, Jing, et al.
Published: (2024)
by: Du, Jing, et al.
Published: (2024)
CDRNP: Cross-Domain Recommendation to Cold-Start Users via Neural Process
by: Li, Xiaodong, et al.
Published: (2024)
by: Li, Xiaodong, et al.
Published: (2024)
Learning User Interests via Reasoning and Distillation for Cross-Domain News Recommendation
by: Zhu, Mengdan, et al.
Published: (2026)
by: Zhu, Mengdan, et al.
Published: (2026)
FARM: Frequency-Aware Model for Cross-Domain Live-Streaming Recommendation
by: Li, Xiaodong, et al.
Published: (2025)
by: Li, Xiaodong, et al.
Published: (2025)
Evaluating and Addressing Fairness Across User Groups in Negative Sampling for Recommender Systems
by: Xuan, Yueqing, et al.
Published: (2023)
by: Xuan, Yueqing, et al.
Published: (2023)
Domain-Aware Cross-Attention for Cross-domain Recommendation
by: Luo, Yuhao, et al.
Published: (2024)
by: Luo, Yuhao, et al.
Published: (2024)
Unlocking the Hidden Treasures: Enhancing Recommendations with Unlabeled Data
by: Zhao, Yuhan, et al.
Published: (2024)
by: Zhao, Yuhan, et al.
Published: (2024)
A Unified Framework for Cross-Domain Recommendation
by: Cao, Jiangxia, et al.
Published: (2024)
by: Cao, Jiangxia, et al.
Published: (2024)
One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems
by: Tang, Zuoli, et al.
Published: (2023)
by: Tang, Zuoli, et al.
Published: (2023)
Fairness and Diversity in Recommender Systems: A Survey
by: Zhao, Yuying, et al.
Published: (2023)
by: Zhao, Yuying, et al.
Published: (2023)
Context-Aware Disentanglement for Cross-Domain Sequential Recommendation: A Causal View
by: Wang, Xingzi, et al.
Published: (2026)
by: Wang, Xingzi, et al.
Published: (2026)
Can One Embedding Fit All? A Multi-Interest Learning Paradigm Towards Improving User Interest Diversity Fairness
by: Zhao, Yuying, et al.
Published: (2024)
by: Zhao, Yuying, et al.
Published: (2024)
Similar Items
-
The Double-Edged Sword of Knowledge Transfer: Diagnosing and Curing Fairness Pathologies in Cross-Domain Recommendation
by: Zhao, Yuhan, et al.
Published: (2026) -
Causality-Inspired Fair Representation Learning for Multimodal Recommendation
by: Chen, Weixin, et al.
Published: (2023) -
Privacy-Preserving Cross-Domain Sequential Recommendation
by: Lin, Zhaohao, et al.
Published: (2024) -
A Survey on Cross-Domain Sequential Recommendation
by: Chen, Shu, et al.
Published: (2024) -
Leave No One Behind: Enhancing Diversity While Maintaining Accuracy in Social Recommendation
by: Li, Lei, et al.
Published: (2025)