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Symmetric Graph Contrastive Learning against Noisy Views for Recommendation

https://doi.org/10.1145/3722103
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s10462-023-10465-9openalex-snapshot
Knowledge Graphs: Opportunities and Challenges
inferredcites →https://doi.org/10.1080/0022250x.2001.9990249openalex-snapshot
A faster algorithm for betweenness centrality*
inferredcites →https://doi.org/10.1109/cvpr52688.2022.01617openalex-snapshot
Robust Contrastive Learning against Noisy Views
inferredcites →https://doi.org/10.1109/tits.2020.3026025openalex-snapshot
GraphSAGE-Based Traffic Speed Forecasting for Segment Network With Sparse Data
inferredcites →https://doi.org/10.1109/tkde.2012.51openalex-snapshot
Nonnegative Matrix Factorization: A Comprehensive Review
inferredcites →https://doi.org/10.1109/tkde.2021.3070203openalex-snapshot
A Survey on Multi-Task Learning
inferredcites →https://doi.org/10.1109/tkde.2021.3074654openalex-snapshot
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks
inferredcites →https://doi.org/10.1109/tkde.2022.3172903openalex-snapshot
Graph Self-Supervised Learning: A Survey
inferredcites →https://doi.org/10.1109/tkde.2023.3282907openalex-snapshot
Self-Supervised Learning for Recommender Systems: A Survey
inferredcites →https://doi.org/10.1109/tkde.2023.3288135openalex-snapshot
XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.1109/tnnls.2020.2978386openalex-snapshot
A Comprehensive Survey on Graph Neural Networks
inferredcites →https://doi.org/10.1145/3292500.3330961openalex-snapshot
Heterogeneous Graph Neural Network
inferredcites →https://doi.org/10.1145/3292500.3330989openalex-snapshot
KGAT
inferredcites →https://doi.org/10.1145/3397271.3401063openalex-snapshot
LightGCN
inferredcites →https://doi.org/10.1145/3426723openalex-snapshot
Deep Learning for Sequential Recommendation
inferredcites →https://doi.org/10.1145/3477141openalex-snapshot
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators
inferredcites →https://doi.org/10.1145/3477495.3531937openalex-snapshot
Are Graph Augmentations Necessary?
inferredcites →https://doi.org/10.1145/3477495.3531982openalex-snapshot
Geometric Disentangled Collaborative Filtering
inferredcites →https://doi.org/10.1145/3477495.3532009openalex-snapshot
Knowledge Graph Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.1145/3477495.3532058openalex-snapshot
Hypergraph Contrastive Collaborative Filtering
inferredcites →https://doi.org/10.1145/3485447.3512104openalex-snapshot
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning
inferredcites →https://doi.org/10.1145/3488560.3498433openalex-snapshot
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation
inferredcites →https://doi.org/10.1145/3494523openalex-snapshot
A Survey of Machine Learning for Computer Architecture and Systems
inferredcites →https://doi.org/10.1145/3511808.3557317openalex-snapshot
Explanation Guided Contrastive Learning for Sequential Recommendation
inferredcites →https://doi.org/10.1145/3535101openalex-snapshot
Graph Neural Networks in Recommender Systems: A Survey
inferredcites →https://doi.org/10.1145/3539618.3591632openalex-snapshot
AdaMCL: Adaptive Fusion Multi-View Contrastive Learning for Collaborative Filtering
inferredcites →https://doi.org/10.1145/3539618.3591647openalex-snapshot
Candidate-aware Graph Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.1145/3539618.3591665openalex-snapshot
Disentangled Contrastive Collaborative Filtering
inferredcites →https://doi.org/10.1145/3539618.3591691openalex-snapshot
Generative-Contrastive Graph Learning for Recommendation
inferredcites →https://doi.org/10.1145/3539618.3591723openalex-snapshot
Graph Transformer for Recommendation
inferredcites →https://doi.org/10.1145/3543507.3583336openalex-snapshot
Automated Self-Supervised Learning for Recommendation
inferredcites →https://doi.org/10.1145/3543507.3583374openalex-snapshot
Robust Preference-Guided Denoising for Graph based Social Recommendation
inferredcites →https://doi.org/10.1145/3543507.3583513openalex-snapshot
Denoising and Prompt-Tuning for Multi-Behavior Recommendation
inferredcites →https://doi.org/10.1145/3568022openalex-snapshot
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions
inferredcites →https://doi.org/10.1145/3577925openalex-snapshot
Self-Supervised Learning for Videos: A Survey
inferredcites →https://doi.org/10.1145/3580305.3599324openalex-snapshot
Efficient Bi-Level Optimization for Recommendation Denoising
inferredcites →https://doi.org/10.1145/3580305.3599768openalex-snapshot
Adaptive Graph Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.1145/3589334.3645533openalex-snapshot
RecDCL: Dual Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.1145/3589334.3645661openalex-snapshot
Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation
inferredcites →https://doi.org/10.1145/3627158openalex-snapshot
Contrastive Self-supervised Learning in Recommender Systems: A Survey
inferredcites →https://doi.org/10.1145/3637528.3671840openalex-snapshot
Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering
inferredcites →https://doi.org/10.1146/annurev-statistics-030718-104938openalex-snapshot
Statistical Aspects of Wasserstein Distances
inferredcites →https://doi.org/10.1609/aaai.v31i1.10894openalex-snapshot
Robust Loss Functions under Label Noise for Deep Neural Networks
inferredcites →https://doi.org/10.1609/aaai.v33i01.33013558openalex-snapshot
Hypergraph Neural Networks
inferredcites →https://doi.org/10.1609/aaai.v33i01.33015329openalex-snapshot
Explainable Reasoning over Knowledge Graphs for Recommendation
inferredcites →https://doi.org/10.1609/aaai.v34i01.5330openalex-snapshot
Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach
inferredcites →https://doi.org/10.1609/aaai.v35i5.16578openalex-snapshot
Self-Supervised Hypergraph Convolutional Networks for Session-based Recommendation
inferredcites →https://doi.org/10.1609/aaai.v37i9.26275openalex-snapshot
AdaTask: A Task-Aware Adaptive Learning Rate Approach to Multi-Task Learning
inferredcites →https://doi.org/10.1609/aaai.v38i8.28789openalex-snapshot
Temporal Graph Contrastive Learning for Sequential Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2022/333openalex-snapshot
Enhancing Sequential Recommendation with Graph Contrastive Learning
inferredcites →https://doi.org/10.48550/arxiv.1706.02216openalex-snapshot
Inductive Representation Learning on Large Graphs
inferredcites →https://doi.org/10.48550/arxiv.1811.01057openalex-snapshot
Semidefinite relaxations for certifying robustness to adversarial examples
inferredcites →https://doi.org/10.48550/arxiv.1905.01997openalex-snapshot
Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
inferredcites →https://doi.org/10.48550/arxiv.2002.02126openalex-snapshot
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2105.07536openalex-snapshot
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data
inferredcites →https://doi.org/10.48550/arxiv.2112.08679openalex-snapshot
Are Graph Augmentations Necessary? Simple Graph Contrastive Learning for Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2302.05862openalex-snapshot
Denoising and Prompt-Tuning for Multi-Behavior Recommendation
inferredcites →https://doi.org/10.48550/arxiv.2302.08191openalex-snapshot
LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-981-92-0375-8_25openalex-snapshot
Aggregate, Optimize, and Propagate: A Forward-Forward Algorithm Framework for Graph-Based Recommendation
inferred← citeshttps://doi.org/10.1007/978-981-92-3410-3_13openalex-snapshot
DGCLRec: Denoising Graph Contrastive Learning for Recommendation
inferred← citeshttps://doi.org/10.1007/s10489-026-07094-4openalex-snapshot
Conditional guided diffusion model in latent space for social recommendation
inferred← citeshttps://doi.org/10.1016/j.eswa.2026.133680openalex-snapshot
CurvGCL: Curvature-guided graph contrastive learning for reliability-aware recommendation
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.115280openalex-snapshot
Enhancing user cold-start recommendation with graph structures and semantic dependencies
inferred← citeshttps://doi.org/10.1016/j.neucom.2026.135026openalex-snapshot
Long-tail multimodal recommendation via collaborative relationship reconstruction and Gaussian perturbation
inferred← citeshttps://doi.org/10.1016/j.neunet.2026.109453openalex-snapshot
SADRec: Semantic-aligned adversarial diffusion model for multi-behavior recommendation
inferred← citeshttps://doi.org/10.1021/acssynbio.6c00184openalex-snapshot
A Multitask Prediction Framework for CircRNAs, Drugs, and Diseases Based on Multi-View Information Integration and Graph Contrastive Learning
inferred← citeshttps://doi.org/10.1145/3773988openalex-snapshot
A Semi-supervised Co-training Algorithm for Robust Recommendation
inferred← citeshttps://doi.org/10.7717/peerj-cs.3807openalex-snapshot
KGDRec: a multi-graph knowledge-enhanced denoising recommendation algorithm
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