Cover Image

MDiffFR: Modality-Guided Diffusion Generation for Cold-start Items in Federated Recommendation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Fu, Kang, Zhang, Honglei, Zou, Xuechao, Li, Yidong
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TransFR: Transferable Federated Recommendation with Adapter Tuning on Pre-trained Language Models
by: Zhang, Honglei, et al.
Published: (2024)

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

Prompt Tuning for Item Cold-start Recommendation
by: Jiang, Yuezihan, et al.
Published: (2024)

A Tutorial of Personalized Federated Recommender Systems: Recent Advances and Future Directions
by: Jiang, Jing, et al.
Published: (2024)

From Transfer to Collaboration: A Federated Framework for Cross-Market Sequential Recommendation
by: Chen, Jundong, et al.
Published: (2026)

General Item Representation Learning for Cold-start Content Recommendations
by: Kim, Jooeun, et al.
Published: (2024)

M^2VAE: Multi-Modal Multi-View Variational Autoencoder for Cold-start Item Recommendation
by: He, Chuan, et al.
Published: (2025)

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

Selecting User Histories to Generate LLM Users for Cold-Start Item Recommendation
by: Subbaraman, Nachiket, et al.
Published: (2025)

On Inherited Popularity Bias in Cold-Start Item Recommendation
by: Meehan, Gregor, et al.
Published: (2025)

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

Sparse Contrastive Learning for Content-Based Cold Item Recommendation
by: Meehan, Gregor, et al.
Published: (2026)

Adversarial Item Promotion on Visually-Aware Recommender Systems by Guided Diffusion
by: Chen, Lijian, et al.
Published: (2023)

Large Language Models as Data Augmenters for Cold-Start Item Recommendation
by: Wang, Jianling, et al.
Published: (2024)

Learnable Item Tokenization for Generative Recommendation
by: Wang, Wenjie, et al.
Published: (2024)

Learning to Collaborate via Structures: Cluster-Guided Item Alignment for Federated Recommendation
by: Tu, Yuchun, et al.
Published: (2026)

GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items
by: Shen, Chenglei, et al.
Published: (2026)

Modeling Item-Level Dynamic Variability with Residual Diffusion for Bundle Recommendation
by: Zhang, Dong, et al.
Published: (2025)

EpicCBR: Item-Relation-Enhanced Dual-Scenario Contrastive Learning for Cold-Start Bundle Recommendation
by: Li, Yihang, et al.
Published: (2026)

SimRec: Mitigating the Cold-Start Problem in Sequential Recommendation by Integrating Item Similarity
by: Brody, Shaked, et al.
Published: (2024)

RLT4Rec: Reinforcement Learning Transformer for User Cold Start and Item Recommendation
by: Rajapakse, Dilina Chandika, et al.
Published: (2024)

Firzen: Firing Strict Cold-Start Items with Frozen Heterogeneous and Homogeneous Graphs for Recommendation
by: He, Hulingxiao, et al.
Published: (2024)

Adaptive Autoguidance for Item-Side Fairness in Diffusion Recommender Systems
by: Li, Zihan, 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)

Harnessing Light for Cold-Start Recommendations: Leveraging Epistemic Uncertainty to Enhance Performance in User-Item Interactions
by: Xiang, Yang, et al.
Published: (2025)

Dataset and Models for Item Recommendation Using Multi-Modal User Interactions
by: Bruun, Simone Borg, et al.
Published: (2024)

Online Item Cold-Start Recommendation with Popularity-Aware Meta-Learning
by: Luo, Yunze, et al.
Published: (2024)

Item-centric Exploration for Cold Start Problem
by: Wang, Dong, et al.
Published: (2025)

Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal Recommendations
by: Li, Jin, et al.
Published: (2025)

Generative Recommender with End-to-End Learnable Item Tokenization
by: Liu, Enze, et al.
Published: (2024)

Divide-and-Conquer: Cold-Start Bundle Recommendation via Mixture of Diffusion Experts
by: Li, Ming, et al.
Published: (2025)

Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
by: Malitesta, Daniele, et al.
Published: (2024)

IGDMRec: Behavior Conditioned Item Graph Diffusion for Multimodal Recommendation
by: Guo, Ziyuan, et al.
Published: (2025)

Lossless and Privacy-Preserving Graph Convolution Network for Federated Item Recommendation
by: Wu, Guowei, et al.
Published: (2024)

RAGSys: Item-Cold-Start Recommender as RAG System
by: Contal, Emile, et al.
Published: (2024)

VM-Rec: A Variational Mapping Approach for Cold-start User Recommendation
by: Zheng, Linan, et al.
Published: (2023)

Personalized Recommendation Models in Federated Settings: A Survey
by: Zhang, Chunxu, et al.
Published: (2025)

Modality Reliability Guided Multimodal Recommendation
by: Dong, Xue, et al.
Published: (2025)

Cold-start Bundle Recommendation via Popularity-based Coalescence and Curriculum Heating
by: Jeon, Hyunsik, et al.
Published: (2023)

Markovian Pre-Trained Transformer for Next-Item Recommendation
by: Xu, Cong, et al.
Published: (2026)