Imagen de Portada

Blockchain-based Federated Recommendation with Incentive Mechanism

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Chen, Jianhai, Wu, Yanlin, Rong, Dazhong, Yu, Guoyao, Jiang, Lingqi, Liu, Zhenguang, Zhou, Peng, Shen, Rui
Formato:	Preprint
Publicado:	2024
Materias:	Information Retrieval
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Poisoning Deep Learning Based Recommender Model in Federated Learning Scenarios
por: Rong, Dazhong, et al.
Publicado: (2022)

Boosting Knowledge Graph-based Recommendations through Confidence-Aware Augmentation with Large Language Models
por: Cai, Rui, et al.
Publicado: (2025)

AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations
por: Wu, Wei, et al.
Publicado: (2024)

Hierarchical Time-Aware Mixture of Experts for Multi-Modal Sequential Recommendation
por: Zhang, Shengzhe, et al.
Publicado: (2025)

DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives
por: Ding, Leilei, et al.
Publicado: (2024)

Federated Adaptation for Foundation Model-based Recommendations
por: Zhang, Chunxu, et al.
Publicado: (2024)

MLLMRec-R1: Incentivizing Reasoning Capability in Large Language Models for Multimodal Sequential Recommendation
por: Wang, Yu, et al.
Publicado: (2026)

Align$^3$GR: Unified Multi-Level Alignment for LLM-based Generative Recommendation
por: Ye, Wencai, et al.
Publicado: (2025)

A Federated Framework for LLM-based Recommendation
por: Zhao, Jujia, et al.
Publicado: (2024)

Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation
por: Liu, Yu, et al.
Publicado: (2025)

A Unified Framework for Cross-Domain Recommendation
por: Cao, Jiangxia, et al.
Publicado: (2024)

GPFedRec: Graph-guided Personalization for Federated Recommendation
por: Zhang, Chunxu, et al.
Publicado: (2023)

Blockchain-Based Spectrum Resource Securitization via Semi-Fungible Token-Lock
por: Zhou, Zhixian, et al.
Publicado: (2026)

Feature-Indexed Federated Recommendation with Residual-Quantized Codebooks
por: Han, Mingzhe, et al.
Publicado: (2026)

FedUTR: Federated Recommendation with Augmented Universal Textual Representation for Sparse Interaction Scenarios
por: Fu, Kang, et al.
Publicado: (2026)

Federated Consistency- and Complementarity-aware Consensus-enhanced Recommendation
por: Mi, Yunqi, et al.
Publicado: (2025)

Hierarchical Semantic RL: Tackling the Problem of Dynamic Action Space for RL-based Recommendations
por: Wang, Minmao, et al.
Publicado: (2025)

Rankformer: A Graph Transformer for Recommendation based on Ranking Objective
por: Chen, Sirui, et al.
Publicado: (2025)

FedCRF: A Federated Cross-domain Recommendation Method with Semantic-driven Deep Knowledge Fusion
por: Guo, Lei, et al.
Publicado: (2026)

Dataset Condensation for Recommendation
por: Wu, Jiahao, et al.
Publicado: (2023)

Federated User Behavior Modeling for Privacy-Preserving LLM Recommendation
por: Guo, Lei, et al.
Publicado: (2026)

Personalized Federated Recommendation With Knowledge Guidance
por: Lim, Jaehyung, et al.
Publicado: (2025)

R4ec: A Reasoning, Reflection, and Refinement Framework for Recommendation Systems
por: Gu, Hao, et al.
Publicado: (2025)

Internalizing Multi-Agent Reasoning for Accurate and Efficient LLM-based Recommendation
por: Wu, Yang, et al.
Publicado: (2026)

CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
por: Wang, Lixiang, et al.
Publicado: (2026)

CS3: Efficient Online Capability Synergy for Two-Tower Recommendation
por: Wang, Lixiang, et al.
Publicado: (2026)

LLM-Alignment Live-Streaming Recommendation
por: Liu, Yueyang, et al.
Publicado: (2025)

Multifaceted User Modeling in Recommendation: A Federated Foundation Models Approach
por: Zhang, Chunxu, et al.
Publicado: (2024)

When Federated Recommendation Meets Cold-Start Problem: Separating Item Attributes and User Interactions
por: Zhang, Chunxu, et al.
Publicado: (2023)

Federated Learning and Unlearning for Recommendation with Personalized Data Sharing
por: Qu, Liang, et al.
Publicado: (2026)

FedCIA: Federated Collaborative Information Aggregation for Privacy-Preserving Recommendation
por: Han, Mingzhe, et al.
Publicado: (2025)

FedAU2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training
por: Li, Yuyuan, et al.
Publicado: (2025)

BBQRec: Behavior-Bind Quantization for Multi-Modal Sequential Recommendation
por: Li, Kaiyuan, et al.
Publicado: (2025)

FITMM: Adaptive Frequency-Aware Multimodal Recommendation via Information-Theoretic Representation Learning
por: Yang, Wei, et al.
Publicado: (2026)

Large Memory Network for Recommendation
por: Lu, Hui, et al.
Publicado: (2025)

Incentive-Aware Recommender Systems in Two-Sided Markets
por: Dai, Xiaowu, et al.
Publicado: (2022)

GORACS: Group-level Optimal Transport-guided Coreset Selection for LLM-based Recommender Systems
por: Mei, Tiehua, et al.
Publicado: (2025)

Beyond Similarity: Personalized Federated Recommendation with Composite Aggregation
por: Zhang, Honglei, et al.
Publicado: (2024)

Structured Spectral Reasoning for Frequency-Adaptive Multimodal Recommendation
por: Yang, Wei, et al.
Publicado: (2025)

DAS: Dual-Aligned Semantic IDs Empowered Industrial Recommender System
por: Ye, Wencai, et al.
Publicado: (2025)