Federated User Behavior Modeling for Privacy-Preserving LLM Recommendation
Fuente:
arXiv
Saved in:
| Main Authors: | Guo, Lei, Yang, Hongyun, Ren, Pengjie, Chen, Tong, Liu, Hui, Chen, Zhumin |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Privacy-Preserving Sequential Recommendation with Collaborative Confusion
by: Wang, Wei, et al.
Published: (2024)
by: Wang, Wei, et al.
Published: (2024)
Generative News Recommendation
by: Gao, Shen, et al.
Published: (2024)
by: Gao, Shen, et al.
Published: (2024)
Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation
by: Wang, Li, et al.
Published: (2024)
by: Wang, Li, et al.
Published: (2024)
Improving Sequential Recommenders through Counterfactual Augmentation of System Exposure
by: Zhao, Ziqi, et al.
Published: (2025)
by: Zhao, Ziqi, et al.
Published: (2025)
Curriculum Approximate Unlearning for Session-based Recommendation
by: Yang, Liu, et al.
Published: (2025)
by: Yang, Liu, et al.
Published: (2025)
Integrating Chain-of-Thought into Generative Retrieval: A Preliminary Study
by: Zhang, Wenhao, et al.
Published: (2026)
by: Zhang, Wenhao, et al.
Published: (2026)
Uncovering Selective State Space Model's Capabilities in Lifelong Sequential Recommendation
by: Yang, Jiyuan, et al.
Published: (2024)
by: Yang, Jiyuan, et al.
Published: (2024)
Content-Based Collaborative Generation for Recommender Systems
by: Wang, Yidan, et al.
Published: (2024)
by: Wang, Yidan, 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)
Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach
by: Zhang, Chunxu, et al.
Published: (2024)
by: Zhang, Chunxu, et al.
Published: (2024)
Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering
by: Shi, Zhengliang, et al.
Published: (2024)
by: Shi, Zhengliang, et al.
Published: (2024)
FedCIA: Federated Collaborative Information Aggregation for Privacy-Preserving Recommendation
by: Han, Mingzhe, et al.
Published: (2025)
by: Han, Mingzhe, et al.
Published: (2025)
Federated Semantic Learning for Privacy-preserving Cross-domain Recommendation
by: Lu, Ziang, et al.
Published: (2025)
by: Lu, Ziang, et al.
Published: (2025)
Constrained Auto-Regressive Decoding Constrains Generative Retrieval
by: Wu, Shiguang, et al.
Published: (2025)
by: Wu, Shiguang, et al.
Published: (2025)
SA-CAISR: Stage-Adaptive and Conflict-Aware Incremental Sequential Recommendation
by: Song, Xiaomeng, et al.
Published: (2026)
by: Song, Xiaomeng, et al.
Published: (2026)
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services
by: Yuan, Wei, et al.
Published: (2024)
by: Yuan, Wei, et al.
Published: (2024)
ExcluIR: Exclusionary Neural Information Retrieval
by: Zhang, Wenhao, et al.
Published: (2024)
by: Zhang, Wenhao, et al.
Published: (2024)
Towards Personalized Privacy: User-Governed Data Contribution for Federated Recommendation
by: Qu, Liang, et al.
Published: (2024)
by: Qu, Liang, et al.
Published: (2024)
Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents
by: Sun, Weiwei, et al.
Published: (2023)
by: Sun, Weiwei, et al.
Published: (2023)
Replication and Exploration of Generative Retrieval over Dynamic Corpora
by: Zhang, Zhen, et al.
Published: (2025)
by: Zhang, Zhen, et al.
Published: (2025)
Behavior Alignment: A New Perspective of Evaluating LLM-based Conversational Recommender Systems
by: Yang, Dayu, et al.
Published: (2024)
by: Yang, Dayu, et al.
Published: (2024)
User Long-Term Multi-Interest Retrieval Model for Recommendation
by: Meng, Yue, et al.
Published: (2025)
by: Meng, Yue, et al.
Published: (2025)
Privacy-Preserving Cross-Domain Sequential Recommendation
by: Lin, Zhaohao, et al.
Published: (2024)
by: Lin, Zhaohao, et al.
Published: (2024)
PCL: Prompt-based Continual Learning for User Modeling in Recommender Systems
by: Yang, Mingdai, et al.
Published: (2025)
by: Yang, Mingdai, et al.
Published: (2025)
FedCRF: A Federated Cross-domain Recommendation Method with Semantic-driven Deep Knowledge Fusion
by: Guo, Lei, et al.
Published: (2026)
by: Guo, Lei, et al.
Published: (2026)
PDSR: A Privacy-Preserving Diversified Service Recommendation Method on Distributed Data
by: Wang, Lina, et al.
Published: (2024)
by: Wang, Lina, et al.
Published: (2024)
A Multi-Agent Conversational Recommender System
by: Fang, Jiabao, et al.
Published: (2024)
by: Fang, Jiabao, et al.
Published: (2024)
Heterogeneous User Modeling for LLM-based Recommendation
by: Bao, Honghui, et al.
Published: (2025)
by: Bao, Honghui, et al.
Published: (2025)
Federated Adaptation for Foundation Model-based Recommendations
by: Zhang, Chunxu, et al.
Published: (2024)
by: Zhang, Chunxu, et al.
Published: (2024)
Generative Retrieval as Multi-Vector Dense Retrieval
by: Wu, Shiguang, et al.
Published: (2024)
by: Wu, Shiguang, et al.
Published: (2024)
MIM: Multi-modal Content Interest Modeling Paradigm for User Behavior Modeling
by: Yan, Bencheng, et al.
Published: (2025)
by: Yan, Bencheng, et al.
Published: (2025)
UniSAR: Modeling User Transition Behaviors between Search and Recommendation
by: Shi, Teng, et al.
Published: (2024)
by: Shi, Teng, et al.
Published: (2024)
A Federated Framework for LLM-based Recommendation
by: Zhao, Jujia, et al.
Published: (2024)
by: Zhao, Jujia, et al.
Published: (2024)
Multi-agents based User Values Mining for Recommendation
by: Chen, Lijian, et al.
Published: (2025)
by: Chen, Lijian, et al.
Published: (2025)
User Invariant Preference Learning for Multi-Behavior Recommendation
by: Yan, Mingshi, et al.
Published: (2025)
by: Yan, Mingshi, et al.
Published: (2025)
Preserving Privacy and Utility in LLM-Based Product Recommendations
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025)
by: Khezresmaeilzadeh, Tina, et al.
Published: (2025)
MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI Recommendation
by: Wu, Ziqing, et al.
Published: (2024)
by: Wu, Ziqing, et al.
Published: (2024)
Improving Sequential Recommender Systems with Online and In-store User Behavior
by: Ma, Luyi, et al.
Published: (2024)
by: Ma, Luyi, et al.
Published: (2024)
Query-Mixed Interest Extraction and Heterogeneous Interaction: A Scalable CTR Model for Industrial Recommender Systems
by: Wang, Fangye, et al.
Published: (2026)
by: Wang, Fangye, et al.
Published: (2026)
Towards Automatic Sampling of User Behaviors for Sequential Recommender Systems
by: Zhang, Hao, et al.
Published: (2023)
by: Zhang, Hao, et al.
Published: (2023)
Similar Items
-
Privacy-Preserving Sequential Recommendation with Collaborative Confusion
by: Wang, Wei, et al.
Published: (2024) -
Generative News Recommendation
by: Gao, Shen, et al.
Published: (2024) -
Federated User Preference Modeling for Privacy-Preserving Cross-Domain Recommendation
by: Wang, Li, et al.
Published: (2024) -
Improving Sequential Recommenders through Counterfactual Augmentation of System Exposure
by: Zhao, Ziqi, et al.
Published: (2025) -
Curriculum Approximate Unlearning for Session-based Recommendation
by: Yang, Liu, et al.
Published: (2025)