Copertina

TwinCL: A Twin Graph Contrastive Learning Model for Collaborative Filtering

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Chengkai, Wang, Jianling, Caverlee, James
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Flow Matching for Collaborative Filtering
di: Liu, Chengkai, et al.
Pubblicazione: (2025)

Mamba4Rec: Towards Efficient Sequential Recommendation with Selective State Space Models
di: Liu, Chengkai, et al.
Pubblicazione: (2024)

Behavior-Dependent Linear Recurrent Units for Efficient Sequential Recommendation
di: Liu, Chengkai, et al.
Pubblicazione: (2024)

Federated Conversational Recommender System
di: Lin, Allen, et al.
Pubblicazione: (2025)

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

L^2CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering
di: Jin, Xinzhou, et al.
Pubblicazione: (2024)

Countering Mainstream Bias via End-to-End Adaptive Local Learning
di: Pan, Jinhao, et al.
Pubblicazione: (2024)

Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering
di: Wu, Yihong, et al.
Pubblicazione: (2024)

Diffusion-augmented Graph Contrastive Learning for Collaborative Filter
di: Huang, Fan, et al.
Pubblicazione: (2025)

Squeeze and Excitation: A Weighted Graph Contrastive Learning for Collaborative Filtering
di: Chen, Zheyu, et al.
Pubblicazione: (2025)

Intent Propagation Contrastive Collaborative Filtering
di: Li, Haojie, et al.
Pubblicazione: (2026)

Self-supervised Contrastive Learning for Implicit Collaborative Filtering
di: Song, Shipeng, et al.
Pubblicazione: (2024)

Rethinking Contrastive Learning for Graph Collaborative Filtering: Limitations and a Simple Remedy
di: Lee, Geon, et al.
Pubblicazione: (2026)

DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management
di: Yin, Kai, et al.
Pubblicazione: (2025)

Unveiling Contrastive Learning's Capability of Neighborhood Aggregation for Collaborative Filtering
di: Zhang, Yu, et al.
Pubblicazione: (2025)

Lightweight Embeddings for Graph Collaborative Filtering
di: Liang, Xurong, et al.
Pubblicazione: (2024)

Neighborhood-Enhanced Supervised Contrastive Learning for Collaborative Filtering
di: Sun, Peijie, et al.
Pubblicazione: (2024)

Neural Causal Graph Collaborative Filtering
di: Wang, Xiangmeng, et al.
Pubblicazione: (2023)

Disentangled Contrastive Collaborative Filtering
di: Ren, Xubin, et al.
Pubblicazione: (2023)

QAGCF: Graph Collaborative Filtering for Q&A Recommendation
di: Zhang, Changshuo, et al.
Pubblicazione: (2024)

DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management
di: Yin, Kai, et al.
Pubblicazione: (2025)

Feedback Reciprocal Graph Collaborative Filtering
di: Chen, Weijun, et al.
Pubblicazione: (2024)

Graph Signal Diffusion Model for Collaborative Filtering
di: Zhu, Yunqin, et al.
Pubblicazione: (2023)

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning
di: He, Yunhang, et al.
Pubblicazione: (2026)

Barlow Twins for Sequential Recommendation
di: Razvorotnev, Ivan, et al.
Pubblicazione: (2025)

PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering
di: Qin, Yifang, et al.
Pubblicazione: (2024)

Lightweight Embeddings with Graph Rewiring for Collaborative Filtering
di: Liang, Xurong, et al.
Pubblicazione: (2025)

General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
di: Zhang, An, et al.
Pubblicazione: (2024)

Wasserstein Dependent Graph Attention Network for Collaborative Filtering with Uncertainty
di: Li, Haoxuan, et al.
Pubblicazione: (2024)

Dual Contrastive Transformer for Hierarchical Preference Modeling in Sequential Recommendation
di: Huang, Chengkai, et al.
Pubblicazione: (2024)

Improving Collaborative Filtering Recommendation via Graph Learning
di: Wang, Yongyu
Pubblicazione: (2023)

A Gated Hybrid Contrastive Collaborative Filtering Recommendation
di: da Silva, Eduardo Ferreira, et al.
Pubblicazione: (2026)

Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation
di: Xu, Jinfeng, et al.
Pubblicazione: (2024)

Graph Neural Controlled Differential Equations For Collaborative Filtering
di: Xu, Ke, et al.
Pubblicazione: (2025)

Light distillation for Incremental Graph Convolution Collaborative Filtering
di: Fan, X, et al.
Pubblicazione: (2025)

S-Diff: An Anisotropic Diffusion Model for Collaborative Filtering in Spectral Domain
di: Xia, Rui, et al.
Pubblicazione: (2024)

SparseCL: Sparse Contrastive Learning for Contradiction Retrieval
di: Xu, Haike, et al.
Pubblicazione: (2024)

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

Industrial Semantics-Aware Digital Twins: A Hybrid Graph Matching Approach for Asset Administration Shells
di: Metović, Ariana, et al.
Pubblicazione: (2026)

Learning Binarized Representations with Pseudo-positive Sample Enhancement for Efficient Graph Collaborative Filtering
di: Chen, Yankai, et al.
Pubblicazione: (2025)