Model the Dynamic Evolution of Facial Expression from Image Sequences. - Zhaoxin Huan; Lin Shang 001 (PAKDD (2), 2018)

Data-Free Adversarial Perturbations for Practical Black-Box Attack. - Zhaoxin Huan; Yulong Wang; Xiaolu Zhang; Lin Shang 001; Chilin Fu; Jun Zhou 011 (PAKDD (2), 2020)

Micro-Expression Recognition Using Micro-Variation Boosted Heat Areas. - Mingyue Zhang; Zhaoxin Huan; Lin Shang 001 (PRCV (2), 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)

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)

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)

G-Meta: Distributed Meta Learning in GPU Clusters for Large-Scale Recommender Systems. - Youshao Xiao; Shangchun Zhao; Zhenglei Zhou; Zhaoxin Huan; Lin Ju; Xiaolu Zhang; Lin Wang 098; Jun Zhou 011 (CIKM, 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)

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)

Rethinking Memory and Communication Cost for Efficient Large Language Model Training. - Chan Wu; Hanxiao Zhang; Lin Ju; Jinjing Huang; Youshao Xiao; Zhaoxin Huan; Siyuan Li; Fanzhuang Meng; Lei Liang 001; Xiaolu Zhang; Jun Zhou 011 (CoRR, 2023)

One Model for All: Large Language Models are Domain-Agnostic Recommendation Systems. - Zuoli Tang; Zhaoxin Huan; Zihao Li 005; Xiaolu Zhang; Jun Hu; Chilin Fu; Jun Zhou 011; Chenliang Li (CoRR, 2023)

TEXT CAN BE FAIR: Mitigating Popularity Bias with PLMs by Learning Relative Preference. - Zuoli Tang; Zhaoxin Huan; Zihao Li 005; Shirui Hu; Xiaolu Zhang; Jun Zhou 011; Lixin Zou; Chenliang Li (CIKM, 2024)

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes. - Youshao Xiao; Lin Ju; Zhenglei Zhou; Siyuan Li; Zhaoxin Huan; Dalong Zhang; Rujie Jiang; Lin Wang 098; Xiaolu Zhang; Lei Liang 002; Jun Zhou 011 (ICDE, 2024)

Rethinking Memory and Communication Costs for Efficient Data Parallel Training of Large Language Models. - Hanxiao Zhang; Lin Ju; Chan Wu; Jinjing Huang; Youshao Xiao; Zhenglei Zhou; Zhiming Fan; Zhaoxin Huan; Siyuan Li; Fanzhuang Meng; Lei Liang 002; Xiaolu Zhang; et al. (NeurIPS, 2024)

A Merge Sort Based Ranking System for the Evaluation of Large Language Models. - Chenchen Li; Linfeng Shi; Chunyi Zhou; Zhaoxin Huan; Chengfu Tang; Xiaolu Zhang; Xudong Wang; Jun Zhou; Song Liu (ECML/PKDD (9), 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)

Enhancing Sequential Recommendation via LLM-based Semantic Embedding Learning. - Jun Hu; Wenwen Xia; Xiaolu Zhang; Chilin Fu; Weichang Wu; Zhaoxin Huan; Ang Li; Zuoli Tang; Jun Zhou 011 (WWW (Companion Volume), 2024)

AntDT: A Self-Adaptive Distributed Training Framework for Leader and Straggler Nodes. - Youshao Xiao; Lin Ju; Zhenglei Zhou; Siyuan Li; Zhaoxin Huan; Dalong Zhang; Rujie Jiang; Lin Wang 098; Xiaolu Zhang; Lei Liang 001; Jun Zhou 011 (CoRR, 2024)

BOSE: A Systematic Evaluation Method Optimized for Base Models. - Hongzhi Luan; Changxin Tian; Zhaoxin Huan; Xiaolu Zhang; Kunlong Chen; Zhiqiang Zhang; Jun Zhou (ACL (Findings), 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)

Toward Stable and Consistent Evaluation Results: A New Methodology for Base Model Evaluation. - Hongzhi Luan; Changxin Tian; Zhaoxin Huan; Xiaolu Zhang; Kunlong Chen; Zhiqiang Zhang 012; Jun Zhou 011 (CoRR, 2025)

Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs. - Ling Team; Binwei Zeng; Chao Huang; Chao Zhang; Changxin Tian; Cong Chen; Dingnan Jin; Feng Yu; Feng Zhu; Feng Yuan; Fakang Wang; Gangshan Wang; et al. (CoRR, 2025)

Short-Path Prompting in LLMs: Analyzing Reasoning Instability and Solutions for Robust Performance. - Zuoli Tang; Junjie Ou; Kaiqin Hu; Chunwei Wu; Zhaoxin Huan; Chilin Fu; Xiaolu Zhang; Jun Zhou; Chenliang Li (CoRR, 2025)

HORAE: Temporal Multi-Interest Pre-training for Sequential Recommendation. - Shirui Hu; Weichang Wu; Zuoli Tang; Zhaoxin Huan; Lin Wang 098; Xiaolu Zhang; Jun Zhou 011; Lixin Zou; Chenliang Li (ACM Trans. Inf. Syst., 2025)

One Model for All: Large Language Models Are Domain-Agnostic Recommendation Systems. - Zuoli Tang; Zhaoxin Huan; Zihao Li 005; Xiaolu Zhang; Jun Hu; Chilin Fu; Jun Zhou 011; Lixin Zou; Chenliang Li (ACM Trans. Inf. Syst., 2025)