Cover Image

Firzen: Firing Strict Cold-Start Items with Frozen Heterogeneous and Homogeneous Graphs for Recommendation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	He, Hulingxiao, He, Xiangteng, Peng, Yuxin, Shan, Zifei, Su, Xin
Format:	Preprint
Published:	2024
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

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

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)

Graph Neural Patching for Cold-Start Recommendations
by: Chen, Hao, et al.
Published: (2024)

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

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)

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

Cold-Starts in Generative Recommendation: A Reproducibility Study
by: Zhang, Zhen, et al.
Published: (2026)

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

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

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

FELRec: Efficient Handling of Item Cold-Start With Dynamic Representation Learning in Recommender Systems
by: Weimann, Kuba, et al.
Published: (2022)

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

Graph Reasoning for Explainable Cold Start Recommendation
by: Frej, Jibril, et al.
Published: (2024)

Task Aligned Meta-learning based Augmented Graph for Cold-Start Recommendation
by: Shi, Yuxiang, et al.
Published: (2022)

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

LLM Reasoning for Cold-Start Item Recommendation
by: Li, Shijun, et al.
Published: (2025)

Large Language Model Simulator for Cold-Start Recommendation
by: Huang, Feiran, et al.
Published: (2024)

Leveraging Artist Catalogs for Cold-Start Music Recommendation
by: Tamm, Yan-Martin, et al.
Published: (2026)

Temporally and Distributionally Robust Optimization for Cold-Start Recommendation
by: Lin, Xinyu, et al.
Published: (2023)

Warming Up Cold-Start CTR Prediction by Learning Item-Specific Feature Interactions
by: Wang, Yaqing, et al.
Published: (2024)

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

Sharpness-Aware Cross-Domain Recommendation to Cold-Start Users
by: Zeng, Guohang, et al.
Published: (2024)

SaviorRec: Semantic-Behavior Alignment for Cold-Start Recommendation
by: Yao, Yining, et al.
Published: (2025)

Let It Go? Not Quite: Addressing Item Cold Start in Sequential Recommendations with Content-Based Initialization
by: Pembek, Anton, et al.
Published: (2025)

Language-Model Prior Overcomes Cold-Start Items
by: Wang, Shiyu, et al.
Published: (2024)

Addressing Cold Start For next-article Recommendation
by: Elgohary, Omar, et al.
Published: (2025)

LLMTreeRec: Unleashing the Power of Large Language Models for Cold-Start Recommendations
by: Zhang, Wenlin, et al.
Published: (2024)

Are Large Language Models Really Effective for Training-Free Cold-Start Recommendation?
by: Kusano, Genki, et al.
Published: (2025)

FilterLLM: Text-To-Distribution LLM for Billion-Scale Cold-Start Recommendation
by: Liu, Ruochen, et al.
Published: (2025)

GateSID: Adaptive Gating for Semantic-Collaborative Alignment in Cold-Start Recommendation
by: Zhu, Hai, et al.
Published: (2026)

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

Personalized Multi-Interest Modeling for Cross-Domain Recommendation to Cold-Start Users
by: Li, Xiaodong, et al.
Published: (2026)

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

DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation
by: Li, Hourun, et al.
Published: (2024)

MDiffFR: Modality-Guided Diffusion Generation for Cold-start Items in Federated Recommendation
by: Fu, Kang, et al.
Published: (2025)

Hybrid Cold-Start Recommender System for Closure Model Selection in Multiphase Flow Simulations
by: Hänsch, S., et al.
Published: (2026)

Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion
by: Hu, Jiacheng, et al.
Published: (2025)