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

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

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

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

WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction. - Jieming Zhu; Yu Kang 006; Zibin Zheng; Michael R. Lyu (ICWS, 2012)

A Clustering-Based QoS Prediction Approach for Web Service Recommendation. - Jieming Zhu; Yu Kang 006; Zibin Zheng; Michael R. Lyu (ISORC Workshops, 2012)

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

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

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

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

Where do developers log? an empirical study on logging practices in industry. - Qiang Fu 015; Jieming Zhu; Wenlu Hu; Jian-Guang Lou; Rui Ding 001; Qingwei Lin; Dongmei Zhang 001; Tao Xie 001 (ICSE Companion, 2014)

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

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

Learning to Log: Helping Developers Make Informed Logging Decisions. - Jieming Zhu; Pinjia He; Qiang Fu 015; Hongyu Zhang 002; Michael R. Lyu; Dongmei Zhang 001 (ICSE (1), 2015)

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

PAID: Prioritizing app issues for developers by tracking user reviews over versions. - Cuiyun Gao 001; Baoxiang Wang 001; Pinjia He; Jieming Zhu; Yangfan Zhou; Michael R. Lyu (ISSRE, 2015)

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

An Evaluation Study on Log Parsing and Its Use in Log Mining. - Pinjia He; Jieming Zhu; Shilin He; Jian Li 054; Michael R. Lyu (DSN, 2016)

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

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

IntelliAd: assisting mobile app developers in measuring ad costs automatically. - Cuiyun Gao 001; Yichuan Man; Hui Xu 009; Jieming Zhu; Yangfan Zhou; Michael R. Lyu (ICSE (Companion Volume), 2017)

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

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

Software Defect Prediction via Convolutional Neural Network. - Jian Li 054; Pinjia He; Jieming Zhu; Michael R. Lyu (QRS, 2017)

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

Detecting Duplicate Bug Reports with Convolutional Neural Networks. - Qi Xie; Zhiyuan Wen; Jieming Zhu; Cuiyun Gao 001; Zibin Zheng (APSEC, 2018)

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

Towards Automated Log Parsing for Large-Scale Log Data Analysis. - Pinjia He; Jieming Zhu; Shilin He; Jian Li 054; Michael R. Lyu (IEEE Trans. Dependable Secur. Comput., 2018)

Tools and benchmarks for automated log parsing. - Jieming Zhu; Shilin He; Jinyang Liu 002; Pinjia He; Qi Xie; Zibin Zheng; Michael R. Lyu (ICSE (SEIP), 2019)

Logzip: Extracting Hidden Structures via Iterative Clustering for Log Compression. - Jinyang Liu 002; Jieming Zhu; Shilin He; Pinjia He; Zibin Zheng; Michael R. Lyu (ASE, 2019)

Ensembled CTR Prediction via Knowledge Distillation. - Jieming Zhu; Jinyang Liu 002; Weiqi Li; Jincai Lai; Xiuqiang He 001; Liang Chen 001; Zibin Zheng (CIKM, 2020)

Directional Adversarial Training for Recommender Systems. - Yangjun Xu; Liang Chen 001; Fenfang Xie; Weibo Hu; Jieming Zhu; Chuan Chen 001; Zibin Zheng (ECAI, 2020)

Regularized Two-Branch Proposal Networks for Weakly-Supervised Moment Retrieval in Videos. - Zhu Zhang; Zhijie Lin 001; Zhou Zhao 001; Jieming Zhu; Xiuqiang He 001 (ACM Multimedia, 2020)

Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding. - Zhu Zhang; Zhou Zhao 001; Zhijie Lin 001; Jieming Zhu; Xiuqiang He 001 (NeurIPS, 2020)

Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. - Kelong Mao; Xi Xiao; Jieming Zhu; Biao Lu; Ruiming Tang; Xiuqiang He 001 (SIGIR, 2020)

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

FuxiCTR: An Open Benchmark for Click-Through Rate Prediction. - Jieming Zhu; Jinyang Liu 002; Shuai Yang; Qi Zhang 001; Xiuqiang He 001 (CoRR, 2020)

Modeling High-order Interactions across Multi-interests for Micro-video Reommendation (Student Abstract). - Dong Yao; Shengyu Zhang 001; Zhou Zhao 001; Wenyan Fan; Jieming Zhu; Xiuqiang He 001; Fei Wu 001 (AAAI, 2021)

SimpleX: A Simple and Strong Baseline for Collaborative Filtering. - Kelong Mao; Jieming Zhu; Jinpeng Wang; Quanyu Dai; Zhenhua Dong; Xi Xiao; Xiuqiang He 001 (CIKM, 2021)

UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. - Kelong Mao; Jieming Zhu; Xi Xiao; Biao Lu; Zhaowei Wang 002; Xiuqiang He 001 (CIKM, 2021)

Open Benchmarking for Click-Through Rate Prediction. - Jieming Zhu; Jinyang Liu 002; Shuai Yang; Qi Zhang 001; Xiuqiang He 001 (CIKM, 2021)

UNBERT: User-News Matching BERT for News Recommendation. - Qi Zhang 001; Jingjie Li; Qinglin Jia; Chuyuan Wang; Jieming Zhu; Zhaowei Wang 002; Xiuqiang He 001 (IJCAI, 2021)

Why Do We Click: Visual Impression-aware News Recommendation. - Jiahao Xun; Shengyu Zhang 001; Zhou Zhao 001; Jieming Zhu; Qi Zhang 001; Jingjie Li; Xiuqiang He 001; Xiaofei He 001; Tat-Seng Chua; Fei Wu 001 (ACM Multimedia, 2021)

RMBERT: News Recommendation via Recurrent Reasoning Memory Network over BERT. - Qinglin Jia; Jingjie Li; Qi Zhang 001; Xiuqiang He 001; Jieming Zhu (SIGIR, 2021)

Hierarchical Cross-Modal Graph Consistency Learning for Video-Text Retrieval. - Weike Jin; Zhou Zhao 001; Pengcheng Zhang; Jieming Zhu; Xiuqiang He 001; Yueting Zhuang (SIGIR, 2021)

Cross-Batch Negative Sampling for Training Two-Tower Recommenders. - Jinpeng Wang; Jieming Zhu; Xiuqiang He 001 (SIGIR, 2021)

QA4PRF: A Question Answering Based Framework for Pseudo Relevance Feedback. - Handong Ma; Jiawei Hou; Chenxu Zhu; Weinan Zhang 001; Ruiming Tang; Jincai Lai; Jieming Zhu; Xiuqiang He 001; Yong Yu 001 (IEEE Access, 2021)

Modeling High-order Interactions across Multi-interests for Micro-video Reommendation. - Dong Yao; Shengyu Zhang 001; Zhou Zhao 001; Wenyan Fan; Jieming Zhu; Xiuqiang He 001; Fei Wu 001 (CoRR, 2021)

Adaptive Spatio-Temporal Graph Enhanced Vision-Language Representation for Video QA. - Weike Jin; Zhou Zhao 001; Xiaochun Cao; Jieming Zhu; Xiuqiang He 001; Yueting Zhuang (IEEE Trans. Image Process., 2021)

MINER: Multi-Interest Matching Network for News Recommendation. - Jian Li 054; Jieming Zhu; Qiwei Bi; Guohao Cai; Lifeng Shang; Zhenhua Dong; Xin Jiang 002; Qun Liu 001 (ACL (Findings), 2022)

LCD: Adaptive Label Correction for Denoising Music Recommendation. - Quanyu Dai; Yalei Lv; Jieming Zhu; Junjie Ye; Zhenhua Dong; Rui Zhang 003; Shu-Tao Xia; Ruiming Tang (CIKM, 2022)

Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. - Qijiong Liu; Jieming Zhu; Quanyu Dai; Xiaoming Wu 003 (COLING, 2022)

Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross- Modal Denoising Networks. - Wenwen Pan 003; Haonan Shi; Zhou Zhao 001; Jieming Zhu; Xiuqiang He 001; Zhigeng Pan; Lianli Gao; Jun Yu 002; Fei Wu 001; Qi Tian 001 (CVPR, 2022)

M4Singer: A Multi-Style, Multi-Singer and Musical Score Provided Mandarin Singing Corpus. - Lichao Zhang; Ruiqi Li; Shoutong Wang; Liqun Deng; Jinglin Liu; Yi Ren 006; Jinzheng He; Rongjie Huang 001; Jieming Zhu; Xiao Chen; Zhou Zhao 001 (NeurIPS, 2022)

ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. - Guohao Cai; Jieming Zhu; Quanyu Dai; Zhenhua Dong; Xiuqiang He 001; Ruiming Tang; Rui Zhang 003 (SIGIR, 2022)

Multi-Level Interaction Reranking with User Behavior History. - Yunjia Xi; Weiwen Liu; Jieming Zhu; Xilong Zhao; Xinyi Dai; Ruiming Tang; Weinan Zhang 001; Rui Zhang 003; Yong Yu 001 (SIGIR, 2022)

BARS: Towards Open Benchmarking for Recommender Systems. - Jieming Zhu; Quanyu Dai; Liangcai Su; Rong Ma; Jinyang Liu 002; Guohao Cai; Xi Xiao; Rui Zhang 003 (SIGIR, 2022)

PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. - Yi Li; Jieming Zhu; Weiwen Liu; Liangcai Su; Guohao Cai; Qi Zhang 001; Ruiming Tang; Xi Xiao; Xiuqiang He 001 (WWW (Companion Volume), 2022)

Contrastive Learning with Positive-Negative Frame Mask for Music Representation. - Dong Yao; Zhou Zhao 001; Shengyu Zhang 001; Jieming Zhu; Yudong Zhu; Rui Zhang 003; Xiuqiang He 001 (WWW, 2022)

CCL4Rec: Contrast over Contrastive Learning for Micro-video Recommendation. - Shengyu Zhang 001; Bofang Li; Dong Yao; Fuli Feng; Jieming Zhu; Wenyan Fan; Zhou Zhao 001; Xiaofei He 001; Tat-Seng Chua; Fei Wu 001 (CoRR, 2022)

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

Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics. - Jieming Zhu; Shilin He; Pinjia He; Jinyang Liu 002; Michael R. Lyu (ISSRE, 2023)

ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. - Jieming Zhu; Guohao Cai; Junjie Huang; Zhenhua Dong; Ruiming Tang; Weinan Zhang 001 (KDD, 2023)

Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks. - Haoyi Duan; Yan Xia 006; Mingze Zhou; Li Tang; Jieming Zhu; Zhou Zhao 001 (NeurIPS, 2023)

Achieving Cross Modal Generalization with Multimodal Unified Representation. - Yan Xia 006; Hai Huang 013; Jieming Zhu; Zhou Zhao 001 (NeurIPS, 2023)

Data-free Knowledge Distillation for Reusing Recommendation Models. - Cheng Wang 025; Jiacheng Sun; Zhenhua Dong; Jieming Zhu; Zhenguo Li; Ruixuan Li 001; Rui Zhang 003 (RecSys, 2023)

Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. - Liangcai Su; Fan Yan; Jieming Zhu; Xi Xiao; Haoyi Duan; Zhou Zhao 001; Zhenhua Dong; Ruiming Tang (SIGIR, 2023)

DisCover: Disentangled Music Representation Learning for Cover Song Identification. - Jiahao Xun; Shengyu Zhang 001; Yanting Yang; Jieming Zhu; Liqun Deng; Zhou Zhao 001; Zhenhua Dong; Ruiqi Li; Lichao Zhang; Fei Wu 001 (SIGIR, 2023)

FINAL: Factorized Interaction Layer for CTR Prediction. - Jieming Zhu; Qinglin Jia; Guohao Cai; Quanyu Dai; Jingjie Li; Zhenhua Dong; Ruiming Tang; Rui Zhang 003 (SIGIR, 2023)

FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. - Qijiong Liu; Jieming Zhu; Jiahao Wu 004; Tiandeng Wu; Zhenhua Dong; Xiao-Ming Wu 003 (WWW, 2023)

Denoising Multi-modal Sequential Recommenders with Contrastive Learning. - Dong Yao; Shengyu Zhang 001; Zhou Zhao 001; Jieming Zhu; Wenqiao Zhang; Rui Zhang 003; Xiaofei He 001; Fei Wu 001 (CoRR, 2023)

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. - Yunjia Xi; Weiwen Liu; Jianghao Lin; Jieming Zhu; Bo Chen 023; Ruiming Tang; Weinan Zhang 001; Rui Zhang 003; Yong Yu 001 (CoRR, 2023)

Time-aligned Exposure-enhanced Model for Click-Through Rate Prediction. - Hengyu Zhang 001; Chang Meng; Wei Guo 006; Huifeng Guo; Jieming Zhu; Guangpeng Zhao; Ruiming Tang; Xiu Li 001 (CoRR, 2023)

A Large-scale Benchmark for Log Parsing. - Zhihan Jiang; Jinyang Liu 002; Junjie Huang 008; Yichen Li 003; Yintong Huo; Jiazhen Gu; Zhuangbin Chen; Jieming Zhu; Michael R. Lyu (CoRR, 2023)

Only Encode Once: Making Content-based News Recommender Greener. - Qijiong Liu; Jieming Zhu; Quanyu Dai; Xiao-Ming Wu 003 (CoRR, 2023)

Co-evolving Vector Quantization for ID-based Recommendation. - Qijiong Liu; Jiaren Xiao; Lu Fan; Jieming Zhu; Xiao-Ming Wu 003 (CoRR, 2023)

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

Music-PAW: Learning Music Representations via Hierarchical Part-whole Interaction and Contrast. - Dong Yao; Shengyu Zhang 001; Zhou Zhao 001; Jieming Zhu; Liqun Deng; Wenqiao Zhang; Zhenhua Dong; Ruiming Tang; Xin Jiang 002 (CoRR, 2023)

UniEmbedding: Learning Universal Multi-Modal Multi-Domain Item Embeddings via User-View Contrastive Learning. - Boqi Dai; Zhaocheng Du; Jieming Zhu; Jintao Xu; Deqing Zou; Quanyu Dai; Zhenhua Dong; Rui Zhang 003; Hai-Tao Zheng 002 (CIKM, 2024)

EASE: Learning Lightweight Semantic Feature Adapters from Large Language Models for CTR Prediction. - Zexuan Qiu; Jieming Zhu; Yankai Chen 001; Guohao Cai; Weiwen Liu; Zhenhua Dong; Irwin King (CIKM, 2024)

Modeling User Attention in Music Recommendation. - Sunhao Dai; Ninglu Shao; Jieming Zhu; Xiao Zhang 034; Zhenhua Dong; Jun Xu 001; Quanyu Dai; Ji-Rong Wen (ICDE, 2024)

A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We? - Zhihan Jiang; Jinyang Liu 002; Junjie Huang 008; Yichen Li 003; Yintong Huo; Jiazhen Gu; Zhuangbin Chen; Jieming Zhu; Michael R. Lyu (ISSTA, 2024)

Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. - Qijiong Liu; Jieming Zhu; Yanting Yang; Quanyu Dai; Zhaocheng Du; Xiao-Ming Wu 003; Zhou Zhao 001; Rui Zhang 003; Zhenhua Dong (KDD, 2024)

EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration. - Ye Wang 018; Jiahao Xun; Minjie Hong; Jieming Zhu; Tao Jin 004; Wang Lin; Haoyuan Li 002; Linjun Li; Yan Xia 006; Zhou Zhao 001; Zhenhua Dong (KDD, 2024)

Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time. - Haiyuan Zhao; Guohao Cai; Jieming Zhu; Zhenhua Dong; Jun Xu 001; Ji-Rong Wen (KDD, 2024)

Multi-sourced Integrated Ranking with Exposure Fairness. - Yifan Liu 008; Weiwen Liu; Wei Xia 001; Jieming Zhu; Weinan Zhang 001; Zhenhua Dong; Yang Wang 019; Ruiming Tang; Rui Zhang 003; Yong Yu 001 (PAKDD (5), 2024)

A Tutorial on Feature Interpretation in Recommender Systems. - Zhaocheng Du; Chuhan Wu; Qinglin Jia; Jieming Zhu; Xu Chen 017 (RecSys, 2024)

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. - Yunjia Xi; Weiwen Liu; Jianghao Lin; Xiaoling Cai; Hong Zhu 003; Jieming Zhu; Bo Chen 023; Ruiming Tang; Weinan Zhang 001; Yong Yu 001 (RecSys, 2024)

Enhancing News Recommendation with Real-Time Feedback and Generative Sequence Modeling. - Qi Zhang 001; Jieming Zhu; Jiansheng Sun; Guohao Cai; Ruining Yu; Bangzheng He; Liangbi Li (RecSys Challenge, 2024)

CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation. - Jieming Zhu; Mengqun Jin; Qijiong Liu; Zexuan Qiu; Zhenhua Dong; Xiu Li 001 (RecSys, 2024)

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

Recall-Augmented Ranking: Enhancing Click-Through Rate Prediction Accuracy with Cross-Stage Data. - Junjie Huang; Guohao Cai; Jieming Zhu; Zhenhua Dong; Ruiming Tang; Weinan Zhang 001; Yong Yu 001 (WWW (Companion Volume), 2024)

RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction. - Yushen Li; Jinpeng Wang 002; Tao Dai 001; Jieming Zhu; Jun Yuan 008; Rui Zhang 003; Shu-Tao Xia (WWW (Companion Volume), 2024)

Discrete Semantic Tokenization for Deep CTR Prediction. - Qijiong Liu; Hengchang Hu; Jiahao Wu 004; Jieming Zhu; Min-Yen Kan; Xiao-Ming Wu 003 (WWW (Companion Volume), 2024)

Learning Category Trees for ID-Based Recommendation: Exploring the Power of Differentiable Vector Quantization. - Qijiong Liu; Jiaren Xiao; Lu Fan; Jieming Zhu; Xiao-Ming Wu 003 (WWW, 2024)

Benchmarking News Recommendation in the Era of Green AI. - Qijiong Liu; Jieming Zhu; Quanyu Dai; Xiao-Ming Wu 003 (WWW (Companion Volume), 2024)

PMG : Personalized Multimodal Generation with Large Language Models. - Xiaoteng Shen; Rui Zhang 003; Xiaoyan Zhao 005; Jieming Zhu; Xi Xiao (WWW, 2024)

MART: Learning Hierarchical Music Audio Representations with Part-Whole Transformer. - Dong Yao; Jieming Zhu; Jiahao Xun; Shengyu Zhang 001; Zhou Zhao 001; Liqun Deng; Wenqiao Zhang; Zhenhua Dong; Xin Jiang 002 (WWW (Companion Volume), 2024)

Multimodal Pretraining and Generation for Recommendation: A Tutorial. - Jieming Zhu; Xin Zhou 008; Chuhan Wu; Rui Zhang 003; Zhenhua Dong (WWW (Companion Volume), 2024)

Unlocking the Potential of Multimodal Unified Discrete Representation through Training-Free Codebook Optimization and Hierarchical Alignment. - Hai Huang 013; Yan Xia 006; Shengpeng Ji; Shulei Wang; Hanting Wang; Jieming Zhu; Zhenhua Dong; Zhou Zhao 001 (CoRR, 2024)

A Survey on the Memory Mechanism of Large Language Model based Agents. - Zeyu Zhang 007; Xiaohe Bo; Chen Ma 001; Rui Li 086; Xu Chen 017; Quanyu Dai; Jieming Zhu; Zhenhua Dong; Ji-Rong Wen (CoRR, 2024)

Contrastive Quantization based Semantic Code for Generative Recommendation. - Mengqun Jin; Zexuan Qiu; Jieming Zhu; Zhenhua Dong; Xiu Li 001 (CoRR, 2024)

Vector Quantization for Recommender Systems: A Review and Outlook. - Qijiong Liu; Xiaoyu Dong; Jiaren Xiao; Nuo Chen 004; Hengchang Hu; Jieming Zhu; Chenxu Zhu; Tetsuya Sakai; Xiao-Ming Wu 003 (CoRR, 2024)

Multimodal Pretraining and Generation for Recommendation: A Tutorial. - Jieming Zhu; Chuhan Wu; Rui Zhang 003; Zhenhua Dong (CoRR, 2024)

EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration. - Ye Wang 018; Jiahao Xun; Mingjie Hong; Jieming Zhu; Tao Jin 004; Wang Lin; Haoyuan Li 002; Linjun Li; Yan Xia 006; Zhou Zhao 001; Zhenhua Dong (CoRR, 2024)

ACE: A Generative Cross-Modal Retrieval Framework with Coarse-To-Fine Semantic Modeling. - Minghui Fang 002; Shengpeng Ji; Jialong Zuo; Hai Huang 013; Yan Xia 006; Jieming Zhu; Xize Cheng; Xiaoda Yang; Wenrui Liu 003; Gang Wang; Zhenhua Dong; Zhou Zhao 001 (CoRR, 2024)

Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation. - Jiachen Zhu 001; Jianghao Lin; Xinyi Dai; Bo Chen 023; Rong Shan; Jieming Zhu; Ruiming Tang; Yong Yu 001; Weinan Zhang 001 (CoRR, 2024)

Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models. - Yunjia Xi; Weiwen Liu; Jianghao Lin; Muyan Weng; Xiaoling Cai; Hong Zhu 003; Jieming Zhu; Bo Chen 023; Ruiming Tang; Yong Yu 001; Weinan Zhang 001 (CoRR, 2024)

STORE: Streamlining Semantic Tokenization and Generative Recommendation with A Single LLM. - Qijiong Liu; Jieming Zhu; Lu Fan; Zhou Zhao 001; Xiao-Ming Wu 003 (CoRR, 2024)

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

MemSim: A Bayesian Simulator for Evaluating Memory of LLM-based Personal Assistants. - Zeyu Zhang 007; Quanyu Dai; Luyu Chen; Zeren Jiang; Rui Li 086; Jieming Zhu; Xu Chen 017; Yi Xie; Zhenhua Dong; Ji-Rong Wen (CoRR, 2024)

An Automatic Graph Construction Framework based on Large Language Models for Recommendation. - Rong Shan; Jianghao Lin; Chenxu Zhu; Bo Chen 023; Menghui Zhu; Kangning Zhang; Jieming Zhu; Ruiming Tang; Yong Yu 001; Weinan Zhang 001 (CoRR, 2024)

Exploiting counter-examples for active learning with partial labels. - Fei Zhang; Yunjie Ye; Lei Feng 006; Zhongwen Rao; Jieming Zhu; Marcus Kalander; Chen Gong 002; Jianye Hao; Bo Han 003 (Mach. Learn., 2024)

EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models. - Guanghao Meng; Sunan He; Jinpeng Wang 002; Tao Dai 001; Letian Zhang; Jieming Zhu; Qing Li 006; Gang Wang; Rui Zhang 003; Yong Jiang 001 (AAAI, 2025)

CART: A Generative Cross-Modal Retrieval Framework With Coarse-To-Fine Semantic Modeling. - Minghui Fang 002; Shengpeng Ji; Jialong Zuo; Hai Huang 013; Yan Xia 006; Jieming Zhu; Xize Cheng; Xiaoda Yang; Wenrui Liu 003; Gang Wang; Zhenhua Dong; Zhou Zhao 001 (ACL (1), 2025)

Enhancing Multimodal Unified Representations for Cross Modal Generalization. - Hai Huang 013; Yan Xia 006; Shengpeng Ji; Shulei Wang; Hanting Wang; Minghui Fang 002; Jieming Zhu; Zhenhua Dong; Sashuai Zhou; Zhou Zhao 001 (ACL (Findings), 2025)

Towards Transformer-Based Aligned Generation with Self-Coherence Guidance. - Shulei Wang; Wang Lin; Hai Huang 013; Hanting Wang; Sihang Cai; WenKang Han; Tao Jin 004; Jingyuan Chen; Jiacheng Sun; Jieming Zhu; Zhou Zhao 001 (CVPR, 2025)

Unsupervised Domain Adaptive Visual Question Answering in the Era of Multi-Modal Large Language Models. - Weixi Weng; Rui Zhang; Xiaojun Meng; Jieming Zhu; Qun Liu 001; Chun Yuan (WACV, 2025)

MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising. - Quanyu Dai; Jiaren Xiao; Zhaocheng Du; Jieming Zhu; Chengxiao Luo; Xiao-Ming Wu 003; Zhenhua Dong (WWW, 2025)

EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration. - Minjie Hong; Yan Xia 006; Zehan Wang 001; Jieming Zhu; Ye Wang 018; Sihang Cai; Xiaoda Yang; Quanyu Dai; Zhenhua Dong; Zhimeng Zhang; Zhou Zhao 001 (WWW, 2025)

Progressive Collaborative and Semantic Knowledge Fusion for Generative Recommendation. - Longtao Xiao; Haozhao Wang; Cheng Wang 025; Linfei Ji; Yifan Wang; Jieming Zhu; Zhenhua Dong; Rui Zhang 003; Ruixuan Li 001 (CoRR, 2025)

A Survey of Personalized Large Language Models: Progress and Future Directions. - Jiahong Liu 001; Zexuan Qiu; Zhongyang Li; Quanyu Dai; Jieming Zhu; Minda Hu; Menglin Yang 005; Irwin King (CoRR, 2025)

Benchmarking LLMs in Recommendation Tasks: A Comparative Evaluation with Conventional Recommenders. - Qijiong Liu; Jieming Zhu; Lu Fan; Kun Wang 042; Hengchang Hu; Wei Guo; Yong Liu; Xiao-Ming Wu 003 (CoRR, 2025)

Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction. - Honghao Li; Yiwen Zhang 001; Yi Zhang 103; Lei Sang 001; Jieming Zhu (CoRR, 2025)

Device-Cloud Collaborative Correction for On-Device Recommendation. - Tianyu Zhan; Shengyu Zhang 001; Zheqi Lv; Jieming Zhu; Jiwei Li 001; Fan Wu 006; Fei Wu 001 (CoRR, 2025)

Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval. - Ruofan Hu; Yan Xia 006; Minjie Hong; Jieming Zhu; Bo Chen 023; Xiaoda Yang; Minghui Fang 002; Tao Jin 004 (CoRR, 2025)

Act-With-Think: Chunk Auto-Regressive Modeling for Generative Recommendation. - Yifan Wang; Weinan Gan; Longtao Xiao; Jieming Zhu; Heng Chang; Haozhao Wang; Rui Zhang 003; Zhenhua Dong; Ruiming Tang; Ruixuan Li 001 (CoRR, 2025)

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