Yu Song

19 papers A* 3A 2Journal 11Unranked 3
YearRankTypeTitle / Venue / Authors
2026 — conf
Are Multimodal Embeddings Truly Beneficial for Recommendation? A Deep Dive into Whole vs. Individual Modalities.
ECIR (3)
Yu Ye, Junchen Fu, Yu Song, Kaiwen Zheng, Joemon M. Jose
2026 A* conf
Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation.
AAAI
Yu Song, Zhigang Hua, Yan Xie, Bingheng Li, Jingzhe Liu, Bo Long, Jiliang Tang, Hui Liu
2026 J jnl
Plain Transformers are Surprisingly Powerful Link Predictors.
CoRR
Quang Truong, Yu Song, Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
2025 — conf
A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation.
KDD (2)
Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu
2025 J jnl
A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation.
CoRR
Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu
2025 J jnl
Are Multimodal Embeddings Truly Beneficial for Recommendation? A Deep Dive into Whole vs. Individual Modalities.
CoRR
Yu Ye, Junchen Fu, Yu Song, Kaiwen Zheng, Joemon M. Jose
2025 A conf
GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning.
CIKM
Yu Song, Zhigang Hua, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu
2025 J jnl
GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning.
CoRR
Yu Song, Zhigang Hua, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu
2025 J jnl
Graph Machine Learning in the Era of Large Language Models (LLMs).
ACM Trans. Intell. Syst. Technol.
Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Wenqi Fan, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li
2025 J jnl
Higher-order Structure Boosts Link Prediction on Temporal Graphs.
CoRR
Jingzhe Liu, Zhigang Hua, Yan Xie, Bingheng Li, Harry Shomer, Yu Song, Kaveh Hassani, Jiliang Tang
2024 — conf
A Pure Transformer Pretraining Framework on Text-Attributed Graphs.
LoG
Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
2024 J jnl
A Pure Transformer Pretraining Framework on Text-attributed Graphs.
CoRR
Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu
2024 A conf
Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights.
WSDM
Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan
2024 J jnl
Graph Machine Learning in the Era of Large Language Models (LLMs).
CoRR
Wenqi Fan, Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li
2024 A* conf
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights.
NeurIPS
Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
2024 J jnl
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights.
CoRR
Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang
2023 J jnl
Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights.
CoRR
Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan
2023 A* conf
Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited.
SIGIR
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, Yongxin Ni
2023 J jnl
Where to Go Next for Recommender Systems? ID- vs. Modality-based recommender models revisited.
CoRR
Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, Yongxin Ni