Sclera Segmentation Benchmarking Competition in Cross-resolution Environment. - Abhijit Das 001; Umapada Pal 001; Michael Blumenstein; Caiyong Wang; Yong He 009; Yuhao Zhu 003; Zhenan Sun (ICB, 2019)

ScleraSegNet: an Improved U-Net Model with Attention for Accurate Sclera Segmentation. - Caiyong Wang; Yong He 009; Yunfan Liu 001; Zhaofeng He; Ran He 001; Zhenan Sun (ICB, 2019)

Robust feature screening for elliptical copula regression model. - Yong He 009; Liang Zhang; Jiadong Ji; Xinsheng Zhang (J. Multivar. Anal., 2019)

A Lightweight Multi-Label Segmentation Network for Mobile Iris Biometrics. - Caiyong Wang; Yunlong Wang 003; Boqiang Xu; Yong He 009; Zhiwei Dong; Zhenan Sun (ICASSP, 2020)

SSBC 2020: Sclera Segmentation Benchmarking Competition in the Mobile Environment. - Matej Vitek; Abhijit Das 001; Yann Pourcenoux; Alexandre Missler; C. Paumier; Sumanta Das; Ishita De Ghosh; Diego Rafael Lucio; Luiz Antonio Zanlorensi; David Menotti; Fadi Boutros; Naser Damer; et al. (IJCB, 2020)

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

CFS-MTL: A Causal Feature Selection Mechanism for Multi-task Learning via Pseudo-intervention. - Zhongde Chen; Ruize Wu; Cong Jiang; Honghui Li; Xin Dong 012; Can Long; Yong He 009; Lei Cheng 005; Linjian Mo (CIKM, 2022)

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

GDOD: Effective Gradient Descent using Orthogonal Decomposition for Multi-Task Learning. - Xin Dong 012; Ruize Wu; Chao Xiong; Hai Li; Lei Cheng 005; Yong He 009; Shiyou Qian; Jian Cao 001; Linjian Mo (CIKM, 2022)

MASR: A Model-Agnostic Sparse Routing Architecture for Arbitrary Order Feature Sharing in Multi-Task Learning. - Xin Dong 012; Ruize Wu; Chao Xiong; Hai Li; Lei Cheng 005; Yong He 009; Shiyou Qian; Jian Cao 001; Linjian Mo (CIKM, 2022)

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

Mixture of Graph Enhanced Expert Networks for Multi-task Recommendation. - Binbin Hu; Bin Shen; Ruize Wu; Zhiqiang Zhang 012; Yuetian Cao; Yong He 009; Liang Zhang; Linjian Mo; Jun Zhou 011 (PRICAI (3), 2022)

An Industrial Framework for Cold-Start Recommendation in Zero-Shot Scenarios. - Zhaoxin Huan; Gongduo Zhang; Xiaolu Zhang; Jun Zhou 011; Qintong Wu; Lihong Gu; Jinjie Gu; Yong He 009; Yue Zhu; Linjian Mo (SIGIR, 2022)

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

SeqGen: A Sequence Generator via User Side Information for Behavior Sparsity in Recommendation. - Xu Min; Xiaolu Zhang; Bin Shen; Shuhan Wang; Yong He 009; Changsheng Li; Jun Zhou 011 (CIKM, 2023)

DAE: Distribution-Aware Embedding for Numerical Features in Click-Through Rate Prediction. - Bin Shen; Jingran Xu; Xu Min; Zeyu Ke; Yong He 009; Liang Zhang; Xin Dong 012; Linjian Mo (CIKM, 2023)

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

SAMD: An Industrial Framework for Heterogeneous Multi-Scenario Recommendation. - Zhaoxin Huan; Ang Li; Xiaolu Zhang; Xu Min; Jieyu Yang; Yong He 009; Jun Zhou 011 (KDD, 2023)

Uncertainty-based Heterogeneous Privileged Knowledge Distillation for Recommendation System. - Ang Li; Jian Hu 002; Ke Ding; 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; Yong He 009; Ke Ding; Zhaoxin Huan; Xiaolu Zhang; Linjian Mo (SIGIR, 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 009; Liang Zhang; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu; Wenliang Zhong; et al. (CoRR, 2023)

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective. - Binbin Hu; Weifan Wang 005; Shuhan Wang; Ziqi Liu; Bin Shen; Yong He 009; Jiawei Chen 007 (CIKM, 2024)

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

Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors. - Binzong Geng; Zhaoxin Huan; Xiaolu Zhang; Yong He 009; Liang Zhang; Fajie Yuan; Jun Zhou 011; Linjian Mo (SIGIR, 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 009; Liang Zhang; Jun Zhou 011; Linjian Mo; Jinjie Gu; Zhongyi Liu; Wenliang Zhong; et al. (SIGIR, 2024)

Aligned Side Information Fusion Method for Sequential Recommendation. - Shuhan Wang; Bin Shen; Xu Min; Yong He 009; Xiaolu Zhang; Liang Zhang; Jun Zhou 011; Linjian Mo (WWW (Companion Volume), 2024)

The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective. - Binbin Hu; Weifan Wang 005; Hanshu Wang; Ziqi Liu; Bin Shen; Yong He 009; Jiawei Chen 007 (CoRR, 2024)

Singleton CTR Prediction: Towards Single-User Modeling Paradigm with Large Language Models. - Xiyu Chang; Liang Zhang; Yong He 009; Binzong Geng; Ke Ding; 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; Ke Ding; Ziyu Lyu; Guanghu Yuan; Chengming Li; Min Yang 007; Zhaoxin Huan; Bin Shen; Yong He 009; et al. (WWW (Companion Volume), 2025)

CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction. - Zixuan Li; Binzong Geng; Jing Xiong; Yong He 009; Yuxuan Hu; Jian Chen; Dingwei Chen; Xiyu Chang; Liang Zhang; Linjian Mo; Chengming Li; Chuan Yuan; et al. (CoRR, 2025)