EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models. - Meng, Guanghao; He, Sunan; Wang, Jinpeng; Dai, Tao; Zhang, Letian; Zhu, Jieming; Li, Qing; Wang, Gang; Zhang, Rui; Jiang, Yong (2025)

Enhancing Multimodal Unified Representations for Cross Modal Generalization. - Huang, Hai; Xia, Yan; Ji, Shengpeng; Wang, Shulei; Wang, Hanting; Fang, Minghui; Zhu, Jieming; Dong, Zhenhua; Zhou, Sashuai; Zhao, Zhou (2025)

CART: A Generative Cross-Modal Retrieval Framework With Coarse-To-Fine Semantic Modeling. - Fang, Minghui; Ji, Shengpeng; Zuo, Jialong; Huang, Hai; Xia, Yan; Zhu, Jieming; Cheng, Xize; Yang, Xiaoda; Liu, Wenrui; Wang, Gang; Dong, Zhenhua; Zhao, Zhou (2025)

Towards Transformer-Based Aligned Generation with Self-Coherence Guidance. - Wang, Shulei; Lin, Wang; Huang, Hai; Wang, Hanting; Cai, Sihang; Han, WenKang; Jin, Tao; Chen, Jingyuan; Sun, Jiacheng; Zhu, Jieming; Zhao, Zhou (2025)

Unsupervised Domain Adaptive Visual Question Answering in the Era of Multi-Modal Large Language Models. - Weng, Weixi; Zhang, Rui; Meng, Xiaojun; Zhu, Jieming; Liu, Qun; Yuan, Chun (2025)

EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration. - Hong, Minjie; Xia, Yan; Wang, Zehan; Zhu, Jieming; Wang, Ye; Cai, Sihang; Yang, Xiaoda; Dai, Quanyu; Dong, Zhenhua; Zhang, Zhimeng; Zhao, Zhou (2025)

MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising. - Dai, Quanyu; Xiao, Jiaren; Du, Zhaocheng; Zhu, Jieming; Luo, Chengxiao; Wu, Xiao-Ming; Dong, Zhenhua (2025)

Progressive Collaborative and Semantic Knowledge Fusion for Generative Recommendation. - Xiao, Longtao; Wang, Haozhao; Wang, Cheng; Ji, Linfei; Wang, Yifan; Zhu, Jieming; Dong, Zhenhua; Zhang, Rui; Li, Ruixuan (CoRR, 2025)

A Survey of Personalized Large Language Models: Progress and Future Directions. - Liu, Jiahong; Qiu, Zexuan; Li, Zhongyang; Dai, Quanyu; Zhu, Jieming; Hu, Minda; Yang, Menglin; King, Irwin (CoRR, 2025)

EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration. - Hong, Minjie; Xia, Yan; Wang, Zehan; Zhu, Jieming; Wang, Ye; Cai, Sihang; Yang, Xiaoda; Dai, Quanyu; Dong, Zhenhua; Zhang, Zhimeng; Zhao, Zhou (CoRR, 2025)

MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising. - Dai, Quanyu; Xiao, Jiaren; Du, Zhaocheng; Zhu, Jieming; Luo, Chengxiao; Wu, Xiao-Ming; Dong, Zhenhua (CoRR, 2025)

Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders. - Liu, Qijiong; Zhu, Jieming; Fan, Lu; Wang, Kun; Hu, Hengchang; Guo, Wei; Liu, Yong; Wu, Xiao-Ming (CoRR, 2025)

Towards Transformer-Based Aligned Generation with Self-Coherence Guidance. - Wang, Shulei; Lin, Wang; Huang, Hai; Wang, Hanting; Cai, Sihang; Han, WenKang; Jin, Tao; Chen, Jingyuan; Sun, Jiacheng; Zhu, Jieming; Zhao, Zhou (CoRR, 2025)

Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction. - Li, Honghao; Zhang, Yiwen; Zhang, Yi; Sang, Lei; Zhu, Jieming (CoRR, 2025)

EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models. - Meng, Guanghao; He, Sunan; Wang, Jinpeng; Dai, Tao; Zhang, Letian; Zhu, Jieming; Li, Qing; Wang, Gang; Zhang, Rui; Jiang, Yong (CoRR, 2025)

Device-Cloud Collaborative Correction for On-Device Recommendation. - Zhan, Tianyu; Zhang, Shengyu; Lv, Zheqi; Zhu, Jieming; Li, Jiwei; Wu, Fan; Wu, Fei (CoRR, 2025)

Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval. - Hu, Ruofan; Xia, Yan; Hong, Minjie; Zhu, Jieming; Chen, Bo; Yang, Xiaoda; Fang, Minghui; Jin, Tao (CoRR, 2025)

Act-With-Think: Chunk Auto-Regressive Modeling for Generative Recommendation. - Wang, Yifan; Gan, Weinan; Xiao, Longtao; Zhu, Jieming; Chang, Heng; Wang, Haozhao; Zhang, Rui; Dong, Zhenhua; Tang, Ruiming; Li, Ruixuan (CoRR, 2025)

TayFCS: Towards Light Feature Combination Selection for Deep Recommender Systems. - Wang, Xianquan; Du, Zhaocheng; Zhu, Jieming; Wu, Chuhan; Jia, Qinglin; Dong, Zhenhua (CoRR, 2025)

Exploiting counter-examples for active learning with partial labels. - Zhang, Fei; Ye, Yunjie; Feng, Lei; Rao, Zhongwen; Zhu, Jieming; Kalander, Marcus; Gong, Chen; Hao, Jianye; Han, Bo (Mach. Learn., 2024)

UniEmbedding: Learning Universal Multi-Modal Multi-Domain Item Embeddings via User-View Contrastive Learning. - Dai, Boqi; Du, Zhaocheng; Zhu, Jieming; Xu, Jintao; Zou, Deqing; Dai, Quanyu; Dong, Zhenhua; Zhang, Rui; Zheng, Hai-Tao (2024)

EASE: Learning Lightweight Semantic Feature Adapters from Large Language Models for CTR Prediction. - Qiu, Zexuan; Zhu, Jieming; Chen, Yankai; Cai, Guohao; Liu, Weiwen; Dong, Zhenhua; King, Irwin (2024)

Modeling User Attention in Music Recommendation. - Dai, Sunhao; Shao, Ninglu; Zhu, Jieming; Zhang, Xiao; Dong, Zhenhua; Xu, Jun; Dai, Quanyu; Wen, Ji-Rong (2024)

A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We? - Jiang, Zhihan; Liu, Jinyang; Huang, Junjie; Li, Yichen; Huo, Yintong; Gu, Jiazhen; Chen, Zhuangbin; Zhu, Jieming; Lyu, Michael R. (2024)

EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration. - Wang, Ye; Xun, Jiahao; Hong, Minjie; Zhu, Jieming; Jin, Tao; Lin, Wang; Li, Haoyuan; Li, Linjun; Xia, Yan; Zhao, Zhou; Dong, Zhenhua (2024)

Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time. - Zhao, Haiyuan; Cai, Guohao; Zhu, Jieming; Dong, Zhenhua; Xu, Jun; Wen, Ji-Rong (2024)

Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. - Liu, Qijiong; Zhu, Jieming; Yang, Yanting; Dai, Quanyu; Du, Zhaocheng; Wu, Xiao-Ming; Zhao, Zhou; Zhang, Rui; Dong, Zhenhua (2024)

Multi-sourced Integrated Ranking with Exposure Fairness. - Liu, Yifan; Liu, Weiwen; Xia, Wei; Zhu, Jieming; Zhang, Weinan; Dong, Zhenhua; Wang, Yang; Tang, Ruiming; Zhang, Rui; Yu, Yong (2024)

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. - Xi, Yunjia; Liu, Weiwen; Lin, Jianghao; Cai, Xiaoling; Zhu, Hong; Zhu, Jieming; Chen, Bo; Tang, Ruiming; Zhang, Weinan; Yu, Yong (2024)

Enhancing News Recommendation with Real-Time Feedback and Generative Sequence Modeling. - Zhang, Qi; Zhu, Jieming; Sun, Jiansheng; Cai, Guohao; Yu, Ruining; He, Bangzheng; Li, Liangbi (2024)

CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation. - Zhu, Jieming; Jin, Mengqun; Liu, Qijiong; Qiu, Zexuan; Dong, Zhenhua; Li, Xiu (2024)

A Tutorial on Feature Interpretation in Recommender Systems. - Du, Zhaocheng; Wu, Chuhan; Jia, Qinglin; Zhu, Jieming; Chen, Xu (2024)

LightCS: Selecting Quadratic Feature Crosses in Linear Complexity. - Du, Zhaocheng; Chen, Junhao; Jia, Qinglin; Wu, Chuhan; Zhu, Jieming; Dong, Zhenhua; Tang, Ruiming (2024)

Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data. - Huang, Junjie; Cai, Guohao; Zhu, Jieming; Dong, Zhenhua; Tang, Ruiming; Zhang, Weinan; Yu, Yong (2024)

RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction. - Li, Yushen; Wang, Jinpeng; Dai, Tao; Zhu, Jieming; Yuan, Jun; Zhang, Rui; Xia, Shu-Tao (2024)

Discrete Semantic Tokenization for Deep CTR Prediction. - Liu, Qijiong; Hu, Hengchang; Wu, Jiahao; Zhu, Jieming; Kan, Min-Yen; Wu, Xiao-Ming (2024)

MART: Learning Hierarchical Music Audio Representations with Part-Whole Transformer. - Yao, Dong; Zhu, Jieming; Xun, Jiahao; Zhang, Shengyu; Zhao, Zhou; Deng, Liqun; Zhang, Wenqiao; Dong, Zhenhua; Jiang, Xin (2024)

Benchmarking News Recommendation in the Era of Green AI. - Liu, Qijiong; Zhu, Jieming; Dai, Quanyu; Wu, Xiao-Ming (2024)

Multimodal Pretraining and Generation for Recommendation: A Tutorial. - Zhu, Jieming; Zhou, Xin; Wu, Chuhan; Zhang, Rui; Dong, Zhenhua (2024)

Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization. - Liu, Qijiong; Xiao, Jiaren; Fan, Lu; Zhu, Jieming; Wu, Xiao-Ming (2024)

PMG : Personalized Multimodal Generation with Large Language Models. - Shen, Xiaoteng; Zhang, Rui; Zhao, Xiaoyan; Zhu, Jieming; Xiao, Xi (2024)

Benchmarking News Recommendation in the Era of Green AI. - Liu, Qijiong; Zhu, Jieming; Dai, Quanyu; Wu, Xiao-Ming (CoRR, 2024)

Unlocking the Potential of Multimodal Unified Discrete Representation through Training-Free Codebook Optimization and Hierarchical Alignment. - Huang, Hai; Xia, Yan; Ji, Shengpeng; Wang, Shulei; Wang, Hanting; Zhu, Jieming; Dong, Zhenhua; Zhao, Zhou (CoRR, 2024)

Discrete Semantic Tokenization for Deep CTR Prediction. - Liu, Qijiong; Hu, Hengchang; Wu, Jiahao; Zhu, Jieming; Kan, Min-Yen; Wu, Xiao-Ming (CoRR, 2024)

Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. - Liu, Qijiong; Zhu, Jieming; Yang, Yanting; Dai, Quanyu; Du, Zhaocheng; Wu, Xiao-Ming; Zhao, Zhou; Zhang, Rui; Dong, Zhenhua (CoRR, 2024)

RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction. - Li, Yushen; Wang, Jinpeng; Dai, Tao; Zhu, Jieming; Yuan, Jun; Zhang, Rui; Xia, Shu-Tao (CoRR, 2024)

PMG : Personalized Multimodal Generation with Large Language Models. - Shen, Xiaoteng; Zhang, Rui; Zhao, Xiaoyan; Zhu, Jieming; Xiao, Xi (CoRR, 2024)

Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data. - Huang, Junjie; Cai, Guohao; Zhu, Jieming; Dong, Zhenhua; Tang, Ruiming; Zhang, Weinan; Yu, Yong (CoRR, 2024)

A Survey on the Memory Mechanism of Large Language Model based Agents. - Zhang, Zeyu; Bo, Xiaohe; Ma, Chen; Li, Rui; Chen, Xu; Dai, Quanyu; Zhu, Jieming; Dong, Zhenhua; Wen, Ji-Rong (CoRR, 2024)

Contrastive Quantization based Semantic Code for Generative Recommendation. - Jin, Mengqun; Qiu, Zexuan; Zhu, Jieming; Dong, Zhenhua; Li, Xiu (CoRR, 2024)

Vector Quantization for Recommender Systems: A Review and Outlook. - Liu, Qijiong; Dong, Xiaoyu; Xiao, Jiaren; Chen, Nuo; Hu, Hengchang; Zhu, Jieming; Zhu, Chenxu; Sakai, Tetsuya; Wu, Xiao-Ming (CoRR, 2024)

Multimodal Pretraining and Generation for Recommendation: A Tutorial. - Zhu, Jieming; Wu, Chuhan; Zhang, Rui; Dong, Zhenhua (CoRR, 2024)

Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time. - Zhao, Haiyuan; Cai, Guohao; Zhu, Jieming; Dong, Zhenhua; Xu, Jun; Wen, Ji-Rong (CoRR, 2024)

EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration. - Wang, Ye; Xun, Jiahao; Hong, Mingjie; Zhu, Jieming; Jin, Tao; Lin, Wang; Li, Haoyuan; Li, Linjun; Xia, Yan; Zhao, Zhou; Dong, Zhenhua (CoRR, 2024)

ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling. - Fang, Minghui; Ji, Shengpeng; Zuo, Jialong; Huang, Hai; Xia, Yan; Zhu, Jieming; Cheng, Xize; Yang, Xiaoda; Liu, Wenrui; Wang, Gang; Dong, Zhenhua; Zhao, Zhou (CoRR, 2024)

Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation. - Zhu, Jiachen; Lin, Jianghao; Dai, Xinyi; Chen, Bo; Shan, Rong; Zhu, Jieming; Tang, Ruiming; Yu, Yong; Zhang, Weinan (CoRR, 2024)

Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models. - Xi, Yunjia; Liu, Weiwen; Lin, Jianghao; Weng, Muyan; Cai, Xiaoling; Zhu, Hong; Zhu, Jieming; Chen, Bo; Tang, Ruiming; Yu, Yong; Zhang, Weinan (CoRR, 2024)

STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM. - Liu, Qijiong; Zhu, Jieming; Fan, Lu; Zhao, Zhou; Wu, Xiao-Ming (CoRR, 2024)

Learning to Compress Contexts for Efficient Knowledge-based Visual Question Answering. - Weng, Weixi; Zhu, Jieming; Zhang, Hao; Meng, Xiaojun; Zhang, Rui; Yuan, Chun (CoRR, 2024)

MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants. - Zhang, Zeyu; Dai, Quanyu; Chen, Luyu; Jiang, Zeren; Li, Rui; Zhu, Jieming; Chen, Xu; Xie, Yi; Dong, Zhenhua; Wen, Ji-Rong (CoRR, 2024)

An Automatic Graph Construction Framework based on Large Language Models for Recommendation. - Shan, Rong; Lin, Jianghao; Zhu, Chenxu; Chen, Bo; Zhu, Menghui; Zhang, Kangning; Zhu, Jieming; Tang, Ruiming; Yu, Yong; Zhang, Weinan (CoRR, 2024)

FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction. - Mao, Kelong; Zhu, Jieming; Su, Liangcai; Cai, Guohao; Li, Yuru; Dong, Zhenhua (2023)

Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics. - Zhu, Jieming; He, Shilin; He, Pinjia; Liu, Jinyang; Lyu, Michael R. (2023)

ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. - Zhu, Jieming; Cai, Guohao; Huang, Junjie; Dong, Zhenhua; Tang, Ruiming; Zhang, Weinan (2023)

Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks. - Duan, Haoyi; Xia, Yan; Zhou, Mingze; Tang, Li; Zhu, Jieming; Zhao, Zhou (2023)

Achieving Cross Modal Generalization with Multimodal Unified Representation. - Xia, Yan; Huang, Hai; Zhu, Jieming; Zhao, Zhou (2023)

Data-free Knowledge Distillation for Reusing Recommendation Models. - Wang, Cheng; Sun, Jiacheng; Dong, Zhenhua; Zhu, Jieming; Li, Zhenguo; Li, Ruixuan; Zhang, Rui (2023)

DisCover: Disentangled Music Representation Learning for Cover Song Identification. - Xun, Jiahao; Zhang, Shengyu; Yang, Yanting; Zhu, Jieming; Deng, Liqun; Zhao, Zhou; Dong, Zhenhua; Li, Ruiqi; Zhang, Lichao; Wu, Fei (2023)

Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. - Su, Liangcai; Yan, Fan; Zhu, Jieming; Xiao, Xi; Duan, Haoyi; Zhao, Zhou; Dong, Zhenhua; Tang, Ruiming (2023)

FINAL: Factorized Interaction Layer for CTR Prediction. - Zhu, Jieming; Jia, Qinglin; Cai, Guohao; Dai, Quanyu; Li, Jingjie; Dong, Zhenhua; Tang, Ruiming; Zhang, Rui (2023)

FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. - Liu, Qijiong; Zhu, Jieming; Wu, Jiahao; Wu, Tiandeng; Dong, Zhenhua; Wu, Xiao-Ming (2023)

FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. - Liu, Qijiong; Zhu, Jieming; Wu, Jiahao; Wu, Tiandeng; Dong, Zhenhua; Wu, Xiao-Ming (CoRR, 2023)

FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction. - Mao, Kelong; Zhu, Jieming; Su, Liangcai; Cai, Guohao; Li, Yuru; Dong, Zhenhua (CoRR, 2023)

Denoising Multi-modal Sequential Recommenders with Contrastive Learning. - Yao, Dong; Zhang, Shengyu; Zhao, Zhou; Zhu, Jieming; Zhang, Wenqiao; Zhang, Rui; He, Xiaofei; Wu, Fei (CoRR, 2023)

ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. - Zhu, Jieming; Cai, Guohao; Huang, Junjie; Dong, Zhenhua; Tang, Ruiming; Zhang, Weinan (CoRR, 2023)

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. - Xi, Yunjia; Liu, Weiwen; Lin, Jianghao; Zhu, Jieming; Chen, Bo; Tang, Ruiming; Zhang, Weinan; Zhang, Rui; Yu, Yong (CoRR, 2023)

Exploiting Counter-Examples for Active Learning with Partial labels. - Zhang, Fei; Ye, Yunjie; Feng, Lei; Rao, Zhongwen; Zhu, Jieming; Kalander, Marcus; Gong, Chen; Hao, Jianye; Han, Bo (CoRR, 2023)

DisCover: Disentangled Music Representation Learning for Cover Song Identification. - Xun, Jiahao; Zhang, Shengyu; Yang, Yanting; Zhu, Jieming; Deng, Liqun; Zhao, Zhou; Dong, Zhenhua; Li, Ruiqi; Zhang, Lichao; Wu, Fei (CoRR, 2023)

Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction. - Zhang, Hengyu; Meng, Chang; Guo, Wei; Guo, Huifeng; Zhu, Jieming; Zhao, Guangpeng; Tang, Ruiming; Li, Xiu (CoRR, 2023)

A Large-scale Benchmark for Log Parsing. - Jiang, Zhihan; Liu, Jinyang; Huang, Junjie; Li, Yichen; Huo, Yintong; Gu, Jiazhen; Chen, Zhuangbin; Zhu, Jieming; Lyu, Michael R. (CoRR, 2023)

Only Encode Once: Making Content-based News Recommender Greener. - Liu, Qijiong; Zhu, Jieming; Dai, Quanyu; Wu, Xiao-Ming (CoRR, 2023)

Co-evolving Vector Quantization for ID-based Recommendation. - Liu, Qijiong; Xiao, Jiaren; Fan, Lu; Zhu, Jieming; Wu, Xiao-Ming (CoRR, 2023)

Ten Challenges in Industrial Recommender Systems. - Dong, Zhenhua; Zhu, Jieming; Liu, Weiwen; Tang, Ruiming (CoRR, 2023)

Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks. - Duan, Haoyi; Xia, Yan; Zhou, Mingze; Tang, Li; Zhu, Jieming; Zhao, Zhou (CoRR, 2023)

Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. - Su, Liangcai; Yan, Fan; Zhu, Jieming; Xiao, Xi; Duan, Haoyi; Zhao, Zhou; Dong, Zhenhua; Tang, Ruiming (CoRR, 2023)

Music-PAW: Learning Music Representations via Hierarchical Part-whole Interaction and Contrast. - Yao, Dong; Zhang, Shengyu; Zhao, Zhou; Zhu, Jieming; Deng, Liqun; Zhang, Wenqiao; Dong, Zhenhua; Tang, Ruiming; Jiang, Xin (CoRR, 2023)

MINER: Multi-Interest Matching Network for News Recommendation. - Li, Jian; Zhu, Jieming; Bi, Qiwei; Cai, Guohao; Shang, Lifeng; Dong, Zhenhua; Jiang, Xin; Liu, Qun (2022)

LCD: Adaptive Label Correction for Denoising Music Recommendation. - Dai, Quanyu; Lv, Yalei; Zhu, Jieming; Ye, Junjie; Dong, Zhenhua; Zhang, Rui; Xia, Shu-Tao; Tang, Ruiming (2022)

Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. - Liu, Qijiong; Zhu, Jieming; Dai, Quanyu; Wu, Xiaoming (2022)

Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross- Modal Denoising Networks. - Pan, Wenwen; Shi, Haonan; Zhao, Zhou; Zhu, Jieming; He, Xiuqiang; Pan, Zhigeng; Gao, Lianli; Yu, Jun; Wu, Fei; Tian, Qi (2022)

M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus. - Zhang, Lichao; Li, Ruiqi; Wang, Shoutong; Deng, Liqun; Liu, Jinglin; Ren, Yi; He, Jinzheng; Huang, Rongjie; Zhu, Jieming; Chen, Xiao; Zhao, Zhou (2022)

Multi-Level Interaction Reranking with User Behavior History. - Xi, Yunjia; Liu, Weiwen; Zhu, Jieming; Zhao, Xilong; Dai, Xinyi; Tang, Ruiming; Zhang, Weinan; Zhang, Rui; Yu, Yong (2022)

ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. - Cai, Guohao; Zhu, Jieming; Dai, Quanyu; Dong, Zhenhua; He, Xiuqiang; Tang, Ruiming; Zhang, Rui (2022)

BARS: Towards Open Benchmarking for Recommender Systems. - Zhu, Jieming; Dai, Quanyu; Su, Liangcai; Ma, Rong; Liu, Jinyang; Cai, Guohao; Xiao, Xi; Zhang, Rui (2022)

PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. - Li, Yi; Zhu, Jieming; Liu, Weiwen; Su, Liangcai; Cai, Guohao; Zhang, Qi; Tang, Ruiming; Xiao, Xi; He, Xiuqiang (2022)

Contrastive Learning with Positive-Negative Frame Mask for Music Representation. - Yao, Dong; Zhao, Zhou; Zhang, Shengyu; Zhu, Jieming; Zhu, Yudong; Zhang, Rui; He, Xiuqiang (2022)

Contrastive Learning with Positive-Negative Frame Mask for Music Representation. - Yao, Dong; Zhao, Zhou; Zhang, Shengyu; Zhu, Jieming; Zhu, Yudong; Zhang, Rui; He, Xiuqiang (CoRR, 2022)

PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. - Li, Yi; Zhu, Jieming; Liu, Weiwen; Su, Liangcai; Cai, Guohao; Zhang, Qi; Tang, Ruiming; Xiao, Xi; He, Xiuqiang (CoRR, 2022)

Multi-Level Interaction Reranking with User Behavior History. - Xi, Yunjia; Liu, Weiwen; Zhu, Jieming; Zhao, Xilong; Dai, Xinyi; Tang, Ruiming; Zhang, Weinan; Zhang, Rui; Yu, Yong (CoRR, 2022)

ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. - Cai, Guohao; Zhu, Jieming; Dai, Quanyu; Dong, Zhenhua; He, Xiuqiang; Tang, Ruiming; Zhang, Rui (CoRR, 2022)

BARS: Towards Open Benchmarking for Recommender Systems. - Zhu, Jieming; Dai, Quanyu; Su, Liangcai; Ma, Rong; Liu, Jinyang; Cai, Guohao; Xiao, Xi; Zhang, Rui (CoRR, 2022)

CCL4Rec: Contrast over Contrastive Learning for Micro-video Recommendation. - Zhang, Shengyu; Li, Bofang; Yao, Dong; Feng, Fuli; Zhu, Jieming; Fan, Wenyan; Zhao, Zhou; He, Xiaofei; Chua, Tat-Seng; Wu, Fei (CoRR, 2022)

QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback. - Ma, Handong; Hou, Jiawei; Zhu, Chenxu; Zhang, Weinan; Tang, Ruiming; Lai, Jincai; Zhu, Jieming; He, Xiuqiang; Yu, Yong (IEEE Access, 2021)

Adaptive Spatio-Temporal Graph Enhanced Vision-Language Representation for Video QA. - Jin, Weike; Zhao, Zhou; Cao, Xiaochun; Zhu, Jieming; He, Xiuqiang; Zhuang, Yueting (IEEE Trans. Image Process., 2021)

Modeling High-order Interactions across Multi-interests for Micro-video Reommendation (Student Abstract). - Yao, Dong; Zhang, Shengyu; Zhao, Zhou; Fan, Wenyan; Zhu, Jieming; He, Xiuqiang; Wu, Fei (2021)

SimpleX: A Simple and Strong Baseline for Collaborative Filtering. - Mao, Kelong; Zhu, Jieming; Wang, Jinpeng; Dai, Quanyu; Dong, Zhenhua; Xiao, Xi; He, Xiuqiang (2021)

UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. - Mao, Kelong; Zhu, Jieming; Xiao, Xi; Lu, Biao; Wang, Zhaowei; He, Xiuqiang (2021)

Open Benchmarking for Click-Through Rate Prediction. - Zhu, Jieming; Liu, Jinyang; Yang, Shuai; Zhang, Qi; He, Xiuqiang (2021)

UNBERT: User-News Matching BERT for News Recommendation. - Zhang, Qi; Li, Jingjie; Jia, Qinglin; Wang, Chuyuan; Zhu, Jieming; Wang, Zhaowei; He, Xiuqiang (2021)

Why Do We Click: Visual Impression-aware News Recommendation. - Xun, Jiahao; Zhang, Shengyu; Zhao, Zhou; Zhu, Jieming; Zhang, Qi; Li, Jingjie; He, Xiuqiang; He, Xiaofei; Chua, Tat-Seng; Wu, Fei (2021)

Hierarchical Cross-Modal Graph Consistency Learning for Video-Text Retrieval. - Jin, Weike; Zhao, Zhou; Zhang, Pengcheng; Zhu, Jieming; He, Xiuqiang; Zhuang, Yueting (2021)

Cross-Batch Negative Sampling for Training Two-Tower Recommenders. - Wang, Jinpeng; Zhu, Jieming; He, Xiuqiang (2021)

RMBERT: News Recommendation via Recurrent Reasoning Memory Network over BERT. - Jia, Qinglin; Li, Jingjie; Zhang, Qi; He, Xiuqiang; Zhu, Jieming (2021)

Modeling High-order Interactions across Multi-interests for Micro-video Reommendation. - Yao, Dong; Zhang, Shengyu; Zhao, Zhou; Fan, Wenyan; Zhu, Jieming; He, Xiuqiang; Wu, Fei (CoRR, 2021)

SimpleX: A Simple and Strong Baseline for Collaborative Filtering. - Mao, Kelong; Zhu, Jieming; Wang, Jinpeng; Dai, Quanyu; Dong, Zhenhua; Xiao, Xi; He, Xiuqiang (CoRR, 2021)

Why Do We Click: Visual Impression-aware News Recommendation. - Xun, Jiahao; Zhang, Shengyu; Zhao, Zhou; Zhu, Jieming; Zhang, Qi; Li, Jingjie; He, Xiuqiang; He, Xiaofei; Chua, Tat-Seng; Wu, Fei (CoRR, 2021)

UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. - Mao, Kelong; Zhu, Jieming; Xiao, Xi; Lu, Biao; Wang, Zhaowei; He, Xiuqiang (CoRR, 2021)

Cross-Batch Negative Sampling for Training Two-Tower Recommenders. - Wang, Jinpeng; Zhu, Jieming; He, Xiuqiang (CoRR, 2021)

QA4PRF: A Question Answering based Framework for Pseudo Relevance Feedback. - Ma, Handong; Hou, Jiawei; Zhu, Chenxu; Zhang, Weinan; Tang, Ruiming; Lai, Jincai; Zhu, Jieming; He, Xiuqiang; Yu, Yong (CoRR, 2021)

Ensembled CTR Prediction via Knowledge Distillation. - Zhu, Jieming; Liu, Jinyang; Li, Weiqi; Lai, Jincai; He, Xiuqiang; Chen, Liang; Zheng, Zibin (2020)

Directional Adversarial Training for Recommender Systems. - Xu, Yangjun; Chen, Liang; Xie, Fenfang; Hu, Weibo; Zhu, Jieming; Chen, Chuan; Zheng, Zibin (2020)

Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos. - Zhang, Zhu; Lin, Zhijie; Zhao, Zhou; Zhu, Jieming; He, Xiuqiang (2020)

Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding. - Zhang, Zhu; Zhao, Zhou; Lin, Zhijie; Zhu, Jieming; He, Xiuqiang (2020)

Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. - Mao, Kelong; Xiao, Xi; Zhu, Jieming; Lu, Biao; Tang, Ruiming; He, Xiuqiang (2020)

Loghub: A Large Collection of System Log Datasets towards Automated Log Analytics. - He, Shilin; Zhu, Jieming; He, Pinjia; Lyu, Michael R. (CoRR, 2020)

Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos. - Zhang, Zhu; Lin, Zhijie; Zhao, Zhou; Zhu, Jieming; He, Xiuqiang (CoRR, 2020)

Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. - Mao, Kelong; Xiao, Xi; Zhu, Jieming; Lu, Biao; Tang, Ruiming; He, Xiuqiang (CoRR, 2020)

FuxiCTR: An Open Benchmark for Click-Through Rate Prediction. - Zhu, Jieming; Liu, Jinyang; Yang, Shuai; Zhang, Qi; He, Xiuqiang (CoRR, 2020)

Ensembled CTR Prediction via Knowledge Distillation. - Zhu, Jieming; Liu, Jinyang; Li, Weiqi; Lai, Jincai; He, Xiuqiang; Chen, Liang; Zheng, Zibin (CoRR, 2020)

Tools and benchmarks for automated log parsing. - Zhu, Jieming; He, Shilin; Liu, Jinyang; He, Pinjia; Xie, Qi; Zheng, Zibin; Lyu, Michael R. (2019)

Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression. - Liu, Jinyang; Zhu, Jieming; He, Shilin; He, Pinjia; Zheng, Zibin; Lyu, Michael R. (2019)

Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression. - Liu, Jinyang; Zhu, Jieming; He, Shilin; He, Pinjia; Zheng, Zibin; Lyu, Michael R. (CoRR, 2019)

Towards Automated Log Parsing for Large-Scale Log Data Analysis. - He, Pinjia; Zhu, Jieming; He, Shilin; Li, Jian; Lyu, Michael R. (IEEE Trans. Dependable Secur. Comput., 2018)

Detecting Duplicate Bug Reports with Convolutional Neural Networks. - Xie, Qi; Wen, Zhiyuan; Zhu, Jieming; Gao, Cuiyun; Zheng, Zibin (2018)

A Directed Acyclic Graph Approach to Online Log Parsing. - He, Pinjia; Zhu, Jieming; Xu, Pengcheng; Zheng, Zibin; Lyu, Michael R. (CoRR, 2018)

Tools and Benchmarks for Automated Log Parsing. - Zhu, Jieming; He, Shilin; Liu, Jinyang; He, Pinjia; Xie, Qi; Zheng, Zibin; Lyu, Michael R. (CoRR, 2018)

Online QoS Prediction for Runtime Service Adaptation via Adaptive Matrix Factorization. - Zhu, Jieming; He, Pinjia; Zheng, Zibin; Lyu, Michael R. (IEEE Trans. Parallel Distributed Syst., 2017)

IntelliAd: assisting mobile app developers in measuring ad costs automatically. - Gao, Cuiyun; Man, Yichuan; Xu, Hui; Zhu, Jieming; Zhou, Yangfan; Lyu, Michael R. (2017)

CARP: Context-Aware Reliability Prediction of Black-Box Web Services. - Zhu, Jieming; He, Pinjia; Xie, Qi; Zheng, Zibin; Lyu, Michael R. (2017)

Drain: An Online Log Parsing Approach with Fixed Depth Tree. - He, Pinjia; Zhu, Jieming; Zheng, Zibin; Lyu, Michael R. (2017)

Software Defect Prediction via Convolutional Neural Network. - Li, Jian; He, Pinjia; Zhu, Jieming; Lyu, Michael R. (2017)

An Evaluation Study on Log Parsing and Its Use in Log Mining. - He, Pinjia; Zhu, Jieming; He, Shilin; Li, Jian; Lyu, Michael R. (2016)

Asymmetric Correlation Regularized Matrix Factorization for Web Service Recommendation. - Xie, Qi; Zhao, Shenglin; Zheng, Zibin; Zhu, Jieming; Lyu, Michael R. (2016)

Experience Report: System Log Analysis for Anomaly Detection. - He, Shilin; Zhu, Jieming; He, Pinjia; Lyu, Michael R. (2016)

Learning to Log: Helping Developers Make Informed Logging Decisions. - Zhu, Jieming; He, Pinjia; Fu, Qiang; Zhang, Hongyu; Lyu, Michael R.; Zhang, Dongmei (2015)

A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation. - Zhu, Jieming; He, Pinjia; Zheng, Zibin; Lyu, Michael R. (2015)

PAID: Prioritizing app issues for developers by tracking user reviews over versions. - Gao, Cuiyun; Wang, Baoxiang; He, Pinjia; Zhu, Jieming; Zhou, Yangfan; Lyu, Michael R. (2015)

A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation. - Zhu, Jieming; He, Pinjia; Zheng, Zibin; Lyu, Michael R. (CoRR, 2015)

Context-Aware Reliability Prediction of Black-Box Services. - Zhu, Jieming; Zheng, Zibin; Lyu, Michael R. (CoRR, 2015)

Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation. - Zhu, Jieming; He, Pinjia; Zheng, Zibin; Lyu, Michael R. (2014)

Where do developers log? an empirical study on logging practices in industry. - Fu, Qiang; Zhu, Jieming; Hu, Wenlu; Lou, Jian-Guang; Ding, Rui; Lin, Qingwei; Zhang, Dongmei; Xie, Tao (2014)

Location-Based Hierarchical Matrix Factorization for Web Service Recommendation. - He, Pinjia; Zhu, Jieming; Zheng, Zibin; Xu, Jianlong; Lyu, Michael R. (2014)

A Hierarchical Matrix Factorization Approach for Location-Based Web Service QoS Prediction. - He, Pinjia; Zhu, Jieming; Xu, Jianlong; Lyu, Michael R. (2014)

DR2: Dynamic Request Routing for Tolerating Latency Variability in Online Cloud Applications. - Zhu, Jieming; Zheng, Zibin; Lyu, Michael R. (2013)

Service-Generated Big Data and Big Data-as-a-Service: An Overview. - Zheng, Zibin; Zhu, Jieming; Lyu, Michael R. (2013)

Scaling Service-Oriented Applications into Geo-distributed Clouds. - Zhu, Jieming; Zheng, Zibin; Zhou, Yangfan; Lyu, Michael R. (2013)

WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction. - Zhu, Jieming; Kang, Yu; Zheng, Zibin; Lyu, Michael R. (2012)

A Clustering-Based QoS Prediction Approach for Web Service Recommendation. - Zhu, Jieming; Kang, Yu; Zheng, Zibin; Lyu, Michael R. (2012)

Operational Definition Refinement: A Discovery Process. - Zytkow, Jan M.; Zhu, Jieming; Zembowicz, Robert (1992)

The First Phase of Real-World Discovery: Determining Repeatability and Error of Experiments. - Zytkow, Jan M.; Zhu, Jieming; Zembowicz, Robert (1992)

Panel: Application of Empirical Discovery in Knowledge Acquisition. - Zytkow, Jan M.; Zhu, Jieming (1991)

Automated Discovery in a Chemistry Laboratory. - Zytkow, Jan M.; Zhu, Jieming; Hussam, Abul (1990)