Ke Ding

According to our database, Ke Ding authored at least 15 papers between 2021 and 2026.

Collaborative distances:

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

2026

Trie-Aware Transformers for Generative Recommendation.

Zhenxiang Xu, Jiawei Chen, Sirui Chen, Yong He, Jieyu Yang, Chuan Yuan, Ke Ding, Can Wang

CoRR, February, 2026

2025

EGRec: Leveraging Generative Rich Intents for Enhanced Recommendation with Large Language Models.

Zhaorui Lian, Binzong Geng, Xiyu Chang, Yu Zhang, Ke Ding, Ziyu Lyu, Guanghu Yuan, Chengming Li, Min Yang, Zhaoxin Huan, Bin Shen, Yong He, Linjian Mo, Liang Zhang, Xing Zhu

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

Singleton CTR Prediction: Towards Single-User Modeling Paradigm with Large Language Models.

Xiyu Chang, Liang Zhang, Yong He, Binzong Geng, Ke Ding, Xing Zhu, Jian Cao, Linjian Mo

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

Contrastive Scenario-Aware Meta Prompting for Multi-scenario Recommendation.

Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He

Proceedings of the Database Systems for Advanced Applications, 2025

2024

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset.

Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang, Chenliang Li, Fajie Yuan

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

MMLRec: A Unified Multi-Task and Multi-Scenario Learning Benchmark for Recommendation.

Guanghu Yuan, Jieyu Yang, Shujie Li, Mingjie Zhong, Ang Li, Ke Ding, Yong He, Min Yang, Liang Zhang, Xiaolu Zhang, Linjian Mo

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

2023

AntM²C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction.

Zhaoxin Huan, Ke Ding, Ang Li, Xiaolu Zhang, Xu Min, Yong He, Liang Zhang, Jun Zhou, Linjian Mo, Jinjie Gu, Zhongyi Liu, Wenliang Zhong, Guannan Zhang

CoRR, 2023

DCBT: A Simple But Effective Way for Unified Warm and Cold Recommendation.

Jieyu Yang, Liang Zhang, Yong He, Ke Ding, Zhaoxin Huan, Xiaolu Zhang, Linjian Mo

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

Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System.

Ang Li, Jian Hu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Xu Min

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

Global-Aware Model-Free Self-distillation for Recommendation System.

Ang Li, Jian Hu, Wei Lu, Ke Ding, Xiaolu Zhang, Jun Zhou, Yong He, Liang Zhang, Lihong Gu

Proceedings of the Database Systems for Advanced Applications, 2023

MI-DPG: Decomposable Parameter Generation Network Based on Mutual Information for Multi-Scenario Recommendation.

Wenzhuo Cheng, Ke Ding, Xin Dong, Yong He, Liang Zhang, Linjian Mo

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

2022

Task Similarity Aware Meta Learning for Cold-Start Recommendation.

Jieyu Yang, Zhaoxin Huan, Yong He, Ke Ding, Liang Zhang, Xiaolu Zhang, Jun Zhou, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

GFlow-FT: Pick a Child Network via Gradient Flow for Efficient Fine-Tuning in Recommendation Systems.

Ke Ding, Yong He, Xin Dong, Jieyu Yang, Liang Zhang, Ang Li, Xiaolu Zhang, Linjian Mo

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Learning to Select Instance: Simultaneous Transfer Learning and Clustering.

Zhaoxin Huan, Yulong Wang, Yong He, Xiaolu Zhang, Chilin Fu, Weichang Wu, Jun Zhou, Ke Ding, Liang Zhang, Linjian Mo

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

MSSM: A Multiple-level Sparse Sharing Model for Efficient Multi-Task Learning.

Ke Ding, Xin Dong, Yong He, Lei Cheng, Chilin Fu, Zhaoxin Huan, Hai Li, Tan Yan, Liang Zhang, Xiaolu Zhang, Linjian Mo

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021