Xiaolong Liu

According to our database, Xiaolong Liu authored at least 23 papers between 2023 and 2026.

Collaborative distances:

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

2026

LoopFM: Learning frOm HistOrical RePresentations of Foundation Model for Recommendation.

Shali Jiang, Hua Zheng, Boyang Liu, Laming Chen, Kenny Lov, Chuanqi Xu, Lisang Ding, Qinghai Zhou, Can Cui, Xiaolong Liu, Xiaoyi Liu, Yasmine Badr, Xin Xu, Jiyan Yang, Ellie Dingqiao Wen, Gerard Jonathan Mugisha Akkerhuis, Chenxiao Guan, Rong Jin, Ruichao Qiu, Xian Chen, Shifu Xu, Zhehui Zhou, Ping Chen, Rui Yang, Haicheng Chen, Xiangge Meng, Song Zhou, Dharak Kharod, Shuyu Xu, Qiang Jin, Qiao Yang, Wankun Zhu, Qin Huang, Yuzhen Huang, Darren Liu, Parish Aggarwal, Hui Zhou, Erzhuo Wang, Shuo Chang, Xiaorui Gan, Wenlin Chen, Santanu Kolay, Huayu Li

CoRR, May, 2026

Kunlun: Establishing Scaling Laws for Massive-Scale Recommendation Systems through Unified Architecture Design.

Bojian Hou, Xiaolong Liu, Xiaoyi Liu, Jiaqi Xu, Yasmine Badr, Mengyue Hang, Sudhanshu Chanpuriya, Junqing Zhou, Yuhang Yang, Han Xu, Qiuling Suo, Laming Chen, Yuxi Hu, Jiasheng Zhang, Huaqing Xiong, Yuzhen Huang, Chao Chen, Yue Dong, Yi Yang, Shuo Chang, Xiaorui Gan, Wenlin Chen, Santanu Kolay, Darren Liu, Jade Nie, Chunzhi Yang, Ellie Wen, Jiyan Yang, Huayu Li

CoRR, February, 2026

2025

Hierarchical LoRA MoE for Efficient CTR Model Scaling.

Zhichen Zeng, Mengyue Hang, Xiaolong Liu, Xiaoyi Liu, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Zhining Liu, Siyang Yuan, Chaofei Yang, Yiqun Liu, Hang Yin, Jiyan Yang, Hanghang Tong

CoRR, October, 2025

Training Large Recommendation Models via Graph-Language Token Alignment.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

CoRR, February, 2025

Training Large Recommendation Models via Graph-Language Tokens Alignment.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

KGARevion: An AI Agent for Knowledge-Intensive Biomedical QA.

Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arné Clevert, Marinka Zitnik

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

InterFormer: Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction.

Zhichen Zeng, Xiaolong Liu, Mengyue Hang, Xiaoyi Liu, Qinghai Zhou, Chaofei Yang, Yiqun Liu, Yichen Ruan, Laming Chen, Yuxin Chen, Yujia Hao, Jiaqi Xu, Jade Nie, Xi Liu, Buyun Zhang, Wei Wen, Siyang Yuan, Hang Yin, Xin Zhang, Kai Wang, Wen-Yen Chen, Yiping Han, Huayu Li, Chunzhi Yang, Bo Long, Philip S. Yu, Hanghang Tong, Jiyan Yang

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

2024

A Collaborative Ensemble Framework for CTR Prediction.

Xiaolong Liu, Zhichen Zeng, Xiaoyi Liu, Siyang Yuan, Weinan Song, Mengyue Hang, Yiqun Liu, Chaofei Yang, Donghyun Kim, Wen-Yen Chen, Jiyan Yang, Yiping Han, Rong Jin, Bo Long, Hanghang Tong, Philip S. Yu

CoRR, 2024

InterFormer: Towards Effective Heterogeneous Interaction Learning for Click-Through Rate Prediction.

Zhichen Zeng, Xiaolong Liu, Mengyue Hang, Xiaoyi Liu, Qinghai Zhou, Chaofei Yang, Yiqun Liu, Yichen Ruan, Laming Chen, Yuxin Chen, Yujia Hao, Jiaqi Xu, Jade Nie, Xi Liu, Buyun Zhang, Wei Wen, Siyang Yuan, Kai Wang, Wen-Yen Chen, Yiping Han, Huayu Li, Chunzhi Yang, Bo Long, Philip S. Yu, Hanghang Tong, Jiyan Yang

CoRR, 2024

Knowledge Graph Based Agent for Complex, Knowledge-Intensive QA in Medicine.

Xiaorui Su, Yibo Wang, Shanghua Gao, Xiaolong Liu, Valentina Giunchiglia, Djork-Arné Clevert, Marinka Zitnik

CoRR, 2024

Unified Pretraining for Recommendation via Task Hypergraphs.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

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

Knowledge Graph Context-Enhanced Diversified Recommendation.

Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Mingdai Yang, Chen Wang, Hao Peng, Philip S. Yu

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

Instruction-based Hypergraph Pretraining.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation.

Chen Wang, Ziwei Fan, Liangwei Yang, Mingdai Yang, Xiaolong Liu, Zhiwei Liu, Philip S. Yu

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Collaborative Alignment for Recommendation.

Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Collaborative Contextualization: Bridging the Gap between Collaborative Filtering and Pre-trained Language Model.

Chen Wang, Liangwei Yang, Zhiwei Liu, Xiaolong Liu, Mingdai Yang, Yueqing Liang, Philip S. Yu

CoRR, 2023

DGRec: Graph Neural Network for Recommendation with Diversified Embedding Generation.

Liangwei Yang, Shengjie Wang, Yunzhe Tao, Jiankai Sun, Xiaolong Liu, Philip S. Yu, Taiqing Wang

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Ranking-based Group Identification via Factorized Attention on Social Tripartite Graph.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Group Identification via Transitional Hypergraph Convolution with Cross-view Self-supervised Learning.

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu, Chen Wang, Hao Peng, Philip S. Yu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Graph-based Alignment and Uniformity for Recommendation.

Liangwei Yang, Zhiwei Liu, Chen Wang, Mingdai Yang, Xiaolong Liu, Jing Ma, Philip S. Yu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Dimension Independent Mixup for Hard Negative Sample in Collaborative Filtering.

Xi Wu, Liangwei Yang, Jibing Gong, Chao Zhou, Tianyu Lin, Xiaolong Liu, Philip S. Yu

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Multi-View Graph Convolution for Participant Recommendation.

Xiaolong Liu, Liangwei Yang, Chen Wang, Mingdai Yang, Zhiwei Liu, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2023

Group-Aware Interest Disentangled Dual-Training for Personalized Recommendation.

Xiaolong Liu, Liangwei Yang, Zhiwei Liu, Xiaohan Li, Mingdai Yang, Chen Wang, Philip S. Yu

Proceedings of the IEEE International Conference on Big Data, 2023