Yu Song

According to our database, Yu Song authored at least 12 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

A Reproducibility Study of Multimodal Embeddings for Recommender Systems.

Yu Ye, Junchen Fu, Yu Song, Kaiwen Zheng, Joemon M. Jose

Int. J. Multim. Inf. Retr., June, 2026

Plain Transformers are Surprisingly Powerful Link Predictors.

Quang Truong, Yu Song, Donald Loveland, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang

CoRR, February, 2026

Are Multimodal Embeddings Truly Beneficial for Recommendation? A Deep Dive into Whole vs. Individual Modalities.

Yu Ye, Junchen Fu, Yu Song, Kaiwen Zheng, Joemon M. Jose

Proceedings of the Advances in Information Retrieval, 2026

Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation.

Yu Song, Zhigang Hua, Yan Xie, Bingheng Li, Jingzhe Liu, Bo Long, Jiliang Tang, Hui Liu

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Graph Machine Learning in the Era of Large Language Models (LLMs).

Shijie Wang, Jiani Huang, Zhikai Chen, Yu Song, Wenzhuo Tang, Haitao Mao, Wenqi Fan, Hui Liu, Xiaorui Liu, Dawei Yin, Qing Li

ACM Trans. Intell. Syst. Technol., October, 2025

Higher-order Structure Boosts Link Prediction on Temporal Graphs.

Jingzhe Liu, Zhigang Hua, Yan Xie, Bingheng Li, Harry Shomer, Yu Song, Kaveh Hassani, Jiliang Tang

CoRR, May, 2025

A Scalable Pretraining Framework for Link Prediction with Efficient Adaptation.

Yu Song, Zhigang Hua, Harry Shomer, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning.

Yu Song, Zhigang Hua, Yan Xie, Jingzhe Liu, Bo Long, Hui Liu

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

Exploring Adapter-based Transfer Learning for Recommender Systems: Empirical Studies and Practical Insights.

Junchen Fu, Fajie Yuan, Yu Song, Zheng Yuan, Mingyue Cheng, Shenghui Cheng, Jiaqi Zhang, Jie Wang, Yunzhu Pan

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights.

Zhikai Chen, Haitao Mao, Jingzhe Liu, Yu Song, Bingheng Li, Wei Jin, Bahare Fatemi, Anton Tsitsulin, Bryan Perozzi, Hui Liu, Jiliang Tang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

A Pure Transformer Pretraining Framework on Text-Attributed Graphs.

Yu Song, Haitao Mao, Jiachen Xiao, Jingzhe Liu, Zhikai Chen, Wei Jin, Carl Yang, Jiliang Tang, Hui Liu

Proceedings of the Learning on Graphs Conference, 26-29 November 2024, Virtual., 2024

2023

Where to Go Next for Recommender Systems? ID- vs. Modality-based Recommender Models Revisited.

Zheng Yuan, Fajie Yuan, Yu Song, Youhua Li, Junchen Fu, Fei Yang, Yunzhu Pan, Yongxin Ni

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023