Standout Papers

Are Graph Augmentations Necessary? 2022 2026 2023 2024207
  1. Are Graph Augmentations Necessary? (2022)
    Junliang Yu, Hongzhi Yin et al. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
  2. Self-Supervised Learning for Recommender Systems: A Survey (2023)
    Junliang Yu, Hongzhi Yin et al. IEEE Transactions on Knowledge and Data Engineering
  3. XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation (2023)
    Junliang Yu, Xin Xia et al. IEEE Transactions on Knowledge and Data Engineering

Immediate Impact

57 standout
Sub-graph 1 of 19

Citing Papers

Personalized Consumer Federated Recommender System Using Fine-Grained Transformation and Hybrid Information Sharing
2025 Standout
Intrusion detection in metaverse environment internet of things systems by metaheuristics tuned two level framework
2025 Standout
1 intermediate paper

Works of Tong Chen being referenced

Are Graph Augmentations Necessary?
2022 Standout
Graph Embedding for Recommendation against Attribute Inference Attacks
2021

Author Peers

Author Last Decade Papers Cites
Tong Chen 1225 1168 322 94 2.0k
Chao Huang 1213 1005 282 81 1.7k
Yanchi Liu 788 860 250 50 1.5k
Shu Wu 792 782 515 61 1.7k
Fuzhen Zhuang 1720 1111 504 76 2.8k
Scott Sanner 1362 731 449 109 2.4k
Lianghao Xia 1158 1070 260 48 1.6k
Jiajie Xu 794 949 333 104 2.0k
Jing He 684 554 382 206 2.3k
Pengpeng Zhao 723 900 350 77 1.6k
Jeffrey Chan 598 480 237 104 1.6k

All Works

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Rankless by CCL
2026