MSSM: A Multiple-level Sparse Sharing Model for Efficient Multi-Task Learning. - Ke Ding 001; Xin Dong 012; Yong He 009; Lei Cheng 005; Chilin Fu; Zhaoxin Huan; Hai Li; Tan Yan; Liang Zhang 045; Xiaolu Zhang; Linjian Mo (SIGIR, 2021)

Learning to Select Instance: Simultaneous Transfer Learning and Clustering. - Zhaoxin Huan; Yulong Wang; Yong He 009; Xiaolu Zhang; Chilin Fu; Weichang Wu; Jun Zhou 011; Ke Ding 001; Liang Zhang 045; Linjian Mo (SIGIR, 2021)

GFlow-FT: Pick a Child Network via Gradient Flow for Efficient Fine-Tuning in Recommendation Systems. - Ke Ding 001; Yong He 009; Xin Dong 012; Jieyu Yang; Liang Zhang 045; Ang Li 043; Xiaolu Zhang; Linjian Mo (CIKM, 2022)

Task Similarity Aware Meta Learning for Cold-Start Recommendation. - Jieyu Yang; Zhaoxin Huan; Yong He 009; Ke Ding 001; Liang Zhang 045; Xiaolu Zhang; Jun Zhou 011; Linjian Mo (CIKM, 2022)

MI-DPG: Decomposable Parameter Generation Network Based on Mutual Information for Multi-Scenario Recommendation. - Wenzhuo Cheng; Ke Ding 001; Xin Dong 012; Yong He 009; Liang Zhang 045; Linjian Mo (CIKM, 2023)

Global-Aware Model-Free Self-distillation for Recommendation System. - Ang Li 043; Jian Hu 002; Wei Lu 011; Ke Ding 001; Xiaolu Zhang; Jun Zhou 011; Yong He 009; Liang Zhang 045; Lihong Gu (DASFAA (4), 2023)

Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System. - Ang Li 043; Jian Hu 002; Ke Ding 001; Xiaolu Zhang; Jun Zhou 011; Yong He 009; Xu Min (SIGIR, 2023)

DCBT: A Simple But Effective Way for Unified Warm and Cold Recommendation. - Jieyu Yang; Liang Zhang 045; Yong He 009; Ke Ding 001; Zhaoxin Huan; Xiaolu Zhang; Linjian Mo (SIGIR, 2023)

AntM2C: A Large Scale Dataset For Multi-Scenario Multi-Modal CTR Prediction. - Zhaoxin Huan; Ke Ding 001; Ang Li 043; Xiaolu Zhang; Xu Min; Yong He 009; Liang Zhang 045; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu 001; Wenliang Zhong; et al. (CoRR, 2023)

MMLRec: A Unified Multi-Task and Multi-Scenario Learning Benchmark for Recommendation. - Guanghu Yuan; Jieyu Yang; Shujie Li 001; Mingjie Zhong; Ang Li 043; Ke Ding 001; Yong He 009; Min Yang 007; Liang Zhang 045; Xiaolu Zhang; Linjian Mo (CIKM, 2024)

Exploring Multi-Scenario Multi-Modal CTR Prediction with a Large Scale Dataset. - Zhaoxin Huan; Ke Ding 001; Ang Li 043; Xiaolu Zhang; Xu Min; Yong He 009; Liang Zhang 045; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu 001; Wenliang Zhong; et al. (SIGIR, 2024)

Contrastive Scenario-Aware Meta Prompting for Multi-scenario Recommendation. - Ang Li 043; Jian Hu 002; Ke Ding 001; Xiaolu Zhang; Jun Zhou 011; Yong He 009 (DASFAA (6), 2025)

Singleton CTR Prediction: Towards Single-User Modeling Paradigm with Large Language Models. - Xiyu Chang; Liang Zhang 045; Yong He 009; Binzong Geng; Ke Ding 001; Xing Zhu; Jian Cao 001; Linjian Mo (WWW (Companion Volume), 2025)

EGRec: Leveraging Generative Rich Intents for Enhanced Recommendation with Large Language Models. - Zhaorui Lian; Binzong Geng; Xiyu Chang; Yu Zhang 254; Ke Ding 001; Ziyu Lyu; Guanghu Yuan; Chengming Li 004; Min Yang 007; Zhaoxin Huan; Bin Shen; Yong He 009; et al. (WWW (Companion Volume), 2025)

Trie-Aware Transformers for Generative Recommendation. - Zhenxiang Xu; Jiawei Chen 007; Sirui Chen; Yong He 009; Jieyu Yang; Chuan Yuan; Ke Ding 001; Can Wang 001 (CoRR, 2026)