Image de couverture de livre

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	He, Yunhang, Xu, Cong, Zhu, Zhangchi, Yin, Hongzhi, Zhang, Wei
Format:	Preprint
Publié:	2026
Sujets:	Information Retrieval
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Collaborative Filtering Meets Spectrum Shift: Connecting User-Item Interaction with Graph-Structured Side Information
par: He, Yunhang, et autres
Publié: (2025)

Lightweight Embeddings with Graph Rewiring for Collaborative Filtering
par: Liang, Xurong, et autres
Publié: (2025)

Lightweight Embeddings for Graph Collaborative Filtering
par: Liang, Xurong, et autres
Publié: (2024)

PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering
par: Qin, Yifang, et autres
Publié: (2024)

STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation
par: Xu, Cong, et autres
Publié: (2024)

Neural Causal Graph Collaborative Filtering
par: Wang, Xiangmeng, et autres
Publié: (2023)

Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering
par: Wu, Yihong, et autres
Publié: (2024)

Graph Neural Controlled Differential Equations For Collaborative Filtering
par: Xu, Ke, et autres
Publié: (2025)

Squeeze and Excitation: A Weighted Graph Contrastive Learning for Collaborative Filtering
par: Chen, Zheyu, et autres
Publié: (2025)

General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
par: Zhang, An, et autres
Publié: (2024)

AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations
par: Wu, Wei, et autres
Publié: (2024)

QAGCF: Graph Collaborative Filtering for Q&A Recommendation
par: Zhang, Changshuo, et autres
Publié: (2024)

Adaptive Hardness Negative Sampling for Collaborative Filtering
par: Lai, Riwei, et autres
Publié: (2024)

Diffusion-augmented Graph Contrastive Learning for Collaborative Filter
par: Huang, Fan, et autres
Publié: (2025)

A Node-Aware Dynamic Quantization Approach for Graph Collaborative Filtering
par: Li, Lin, et autres
Publié: (2025)

Understanding Embedding Scaling in Collaborative Filtering
par: He, Yicheng, et autres
Publié: (2025)

Graph Signal Diffusion Model for Collaborative Filtering
par: Zhu, Yunqin, et autres
Publié: (2023)

Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation
par: Xu, Jinfeng, et autres
Publié: (2024)

Feedback Reciprocal Graph Collaborative Filtering
par: Chen, Weijun, et autres
Publié: (2024)

Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation
par: Li, Hanyu, et autres
Publié: (2024)

Improving Collaborative Filtering Recommendation via Graph Learning
par: Wang, Yongyu
Publié: (2023)

Break the Optimization Barrier of LLM-Enhanced Recommenders: A Theoretical Analysis and Practical Framework
par: Zhu, Zhangchi, et autres
Publié: (2026)

Preference-Consistent Knowledge Distillation for Recommender System
par: Zhu, Zhangchi, et autres
Publié: (2023)

S-Diff: An Anisotropic Diffusion Model for Collaborative Filtering in Spectral Domain
par: Xia, Rui, et autres
Publié: (2024)

Embed Progressive Implicit Preference in Unified Space for Deep Collaborative Filtering
par: Zhang, Zhongjin, et autres
Publié: (2025)

MixRec: Heterogeneous Graph Collaborative Filtering
par: Xia, Lianghao, et autres
Publié: (2024)

Understanding the Role of Cross-Entropy Loss in Fairly Evaluating Large Language Model-based Recommendation
par: Xu, Cong, et autres
Publié: (2024)

Exploring the Individuality and Collectivity of Intents behind Interactions for Graph Collaborative Filtering
par: Zhang, Yi, et autres
Publié: (2024)

Wasserstein Dependent Graph Attention Network for Collaborative Filtering with Uncertainty
par: Li, Haoxuan, et autres
Publié: (2024)

Towards Unified and Adaptive Cross-Domain Collaborative Filtering via Graph Signal Processing
par: Lee, Jeongeun, et autres
Publié: (2024)

Light distillation for Incremental Graph Convolution Collaborative Filtering
par: Fan, X, et autres
Publié: (2025)

Flow Matching for Collaborative Filtering
par: Liu, Chengkai, et autres
Publié: (2025)

Learning Binarized Representations with Pseudo-positive Sample Enhancement for Efficient Graph Collaborative Filtering
par: Chen, Yankai, et autres
Publié: (2025)

Transparent and Controllable Recommendation Filtering via Multimodal Multi-Agent Collaboration
par: Zhang, Chi, et autres
Publié: (2026)

Fair Augmentation for Graph Collaborative Filtering
par: Boratto, Ludovico, et autres
Publié: (2024)

Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and a Simple Remedy
par: Lee, Geon, et autres
Publié: (2026)

TwinCL: A Twin Graph Contrastive Learning Model for Collaborative Filtering
par: Liu, Chengkai, et autres
Publié: (2024)

Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative Filtering
par: Zhang, Yu, et autres
Publié: (2025)

Large Language Models Enhanced Collaborative Filtering
par: Sun, Zhongxiang, et autres
Publié: (2024)

Disentangled Contrastive Collaborative Filtering
par: Ren, Xubin, et autres
Publié: (2023)