Jieming Zhu
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
92
Venues
27
Active years
1990–2026
Best venue rank
A*
Where they publish
- A*WWW15 papers
- A*SIGIR10 papers
- A*KDD9 papers
- A*AAAI7 papers
- ACIKM7 papers
- AICWS6 papers
- ARecSys5 papers
- A*ACL4 papers
- A*ICSE4 papers
- AISSRE3 papers
- BPAKDD2 papers
- A*CVPR2 papers
- A*EMNLP2 papers
- A*IJCAI2 papers
- AInterspeech2 papers
- AWACV1 paper
- A*ICDE1 paper
- AISSTA1 paper
- BCOLING1 paper
- AECAI1 paper
- CAPSEC1 paper
- CQRS1 paper
- ADSN1 paper
- AICDCS1 paper
- BBigData1 paper
- CISORC1 paper
- A*ICML1 paper
Papers
92 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Suit the Remedy to the Retriever: Interpretable Query Optimization with Retriever Preference Alignment for Vision-Language Retrieval. | Guanghao Meng, Jinpeng Wang, Jieming Zhu, Letian Zhang, Yong Jiang, Dan Zhao, Qing Li |
| 2026 | AAAI | Length-Adaptive Interest Network for Balancing Long and Short Sequence Modeling in CTR Prediction. | Zhicheng Zhang, Zhaocheng Du, Jieming Zhu, Jiwei Tang, Fengyuan Lu, Wang Jiaheng, Song-Li Wu, Qianhui Zhu, Jingyu Li, Hai-Tao Zheng, Zhenhua Dong |
| 2026 | KDD | FCN: Fusing Exponential and Linear Cross Network for Click-Through Rate Prediction. | Honghao Li, Yiwen Zhang, Yi Zhang, Hanwei Li, Lei Sang, Jieming Zhu |
| 2026 | PAKDD | Learning Multi-aspect Item Palette: A Semantic Tokenization Framework for Generative Recommendation. | Qijiong Liu, Jieming Zhu, Zhaocheng Du, Lu Fan, Zhou Zhao, Xiao-Ming Wu |
| 2026 | WWW | FairFS: Addressing Deep Feature Selection Biases for Recommender System. | Xianquan Wang, Zhaocheng Du, Jieming Zhu, Qinglin Jia, Zhenhua Dong, Kai Zhang |
| 2025 | AAAI | EvdCLIP: Improving Vision-Language Retrieval with Entity Visual Descriptions from Large Language Models. | Guanghao Meng, Sunan He, Jinpeng Wang, Tao Dai, Letian Zhang, Jieming Zhu, Qing Li, Gang Wang, Rui Zhang, Yong Jiang |
| 2025 | ACL | CART: A Generative Cross-Modal Retrieval Framework With Coarse-To-Fine Semantic Modeling. | Minghui Fang, Shengpeng Ji, Jialong Zuo, Hai Huang, Yan Xia, Jieming Zhu, Xize Cheng, Xiaoda Yang, Wenrui Liu, Gang Wang, Zhenhua Dong, Zhou Zhao |
| 2025 | ACL | Enhancing Multimodal Unified Representations for Cross Modal Generalization. | Hai Huang, Yan Xia, Shengpeng Ji, Shulei Wang, Hanting Wang, Minghui Fang, Jieming Zhu, Zhenhua Dong, Sashuai Zhou, Zhou Zhao |
| 2025 | ACL | MIRA: Empowering One-Touch AI Services on Smartphones with MLLM-based Instruction Recommendation. | Zhipeng Bian, Jieming Zhu, Xuyang Xie, Quanyu Dai, Zhou Zhao, Zhenhua Dong |
| 2025 | CVPR | Towards Transformer-Based Aligned Generation with Self-Coherence Guidance. | Shulei Wang, Wang Lin, Hai Huang, Hanting Wang, Sihang Cai, WenKang Han, Tao Jin, Jingyuan Chen, Jiacheng Sun, Jieming Zhu, Zhou Zhao |
| 2025 | EMNLP | ICG: Improving Cover Image Generation via MLLM-based Prompting and Personalized Preference Alignment. | Zhipeng Bian, Jieming Zhu, Qijiong Liu, Wang Lin, Guohao Cai, Zhaocheng Du, Jiacheng Sun, Zhou Zhao, Zhenhua Dong |
| 2025 | EMNLP | RecBase: Generative Foundation Model Pretraining for Zero-Shot Recommendation. | Sashuai Zhou, Weinan Gan, Qijiong Liu, Ke Lei, Jieming Zhu, Hai Huang, Yan Xia, Ruiming Tang, Zhenhua Dong, Zhou Zhao |
| 2025 | IJCAI | Device-Cloud Collaborative Correction for On-Device Recommendation. | Tianyu Zhan, Shengyu Zhang, Zheqi Lv, Jieming Zhu, Jiwei Li, Fan Wu, Fei Wu |
| 2025 | Interspeech | GTA: Towards Generative Text-To-Audio Retrieval via Multi-Scale Tokenizer. | Minghui Fang, Shengpeng Ji, Jialong Zuo, Xize Cheng, Wenrui Liu, Xiaoda Yang, Ruofan Hu, Jieming Zhu, Zhou Zhao |
| 2025 | Interspeech | Vela: Scalable Embeddings with Voice Large Language Models for Multimodal Retrieval. | Ruofan Hu, Yan Xia, Minjie Hong, Jieming Zhu, Bo Chen, Xiaoda Yang, Minghui Fang, Tao Jin |
| 2025 | KDD | Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction. | Honghao Li, Yiwen Zhang, Yi Zhang, Lei Sang, Jieming Zhu |
| 2025 | KDD | ROMA: Recommendation-Oriented Language Model Adaptation Using Multi-Modal Multi-Domain Item Sequences. | Xingyu Lu, Jinpeng Wang, Jieming Zhu, Zhicheng Zhang, Deqing Zou, Hai-Tao Zheng, Shu-Tao Xia, Rui Zhang |
| 2025 | KDD | An Automatic Graph Construction Framework based on Large Language Models for Recommendation. | Rong Shan, Jianghao Lin, Chenxu Zhu, Bo Chen, Menghui Zhu, Kangning Zhang, Jieming Zhu, Ruiming Tang, Yong Yu, Weinan Zhang |
| 2025 | KDD | TayFCS: Towards Light Feature Combination Selection for Deep Recommender Systems. | Xianquan Wang, Zhaocheng Du, Jieming Zhu, Chuhan Wu, Qinglin Jia, Zhenhua Dong |
| 2025 | WWW | MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising. | Quanyu Dai, Jiaren Xiao, Zhaocheng Du, Jieming Zhu, Chengxiao Luo, Xiao-Ming Wu, Zhenhua Dong |
| 2025 | WWW | EAGER-LLM: Enhancing Large Language Models as Recommenders through Exogenous Behavior-Semantic Integration. | Minjie Hong, Yan Xia, Zehan Wang, Jieming Zhu, Ye Wang, Sihang Cai, Xiaoda Yang, Quanyu Dai, Zhenhua Dong, Zhimeng Zhang, Zhou Zhao |
| 2025 | WACV | 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, Chun Yuan |
| 2024 | CIKM | 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, Hai-Tao Zheng |
| 2024 | CIKM | EASE: Learning Lightweight Semantic Feature Adapters from Large Language Models for CTR Prediction. | Zexuan Qiu, Jieming Zhu, Yankai Chen, Guohao Cai, Weiwen Liu, Zhenhua Dong, Irwin King |
| 2024 | ICDE | Modeling User Attention in Music Recommendation. | Sunhao Dai, Ninglu Shao, Jieming Zhu, Xiao Zhang, Zhenhua Dong, Jun Xu, Quanyu Dai, Ji-Rong Wen |
| 2024 | ISSTA | A Large-Scale Evaluation for Log Parsing Techniques: How Far Are We? | Zhihan Jiang, Jinyang Liu, Junjie Huang, Yichen Li, Yintong Huo, Jiazhen Gu, Zhuangbin Chen, Jieming Zhu, Michael R. Lyu |
| 2024 | KDD | Multimodal Pretraining, Adaptation, and Generation for Recommendation: A Survey. | Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai, Zhaocheng Du, Xiao-Ming Wu, Zhou Zhao, Rui Zhang, Zhenhua Dong |
| 2024 | KDD | EAGER: Two-Stream Generative Recommender with Behavior-Semantic Collaboration. | Ye Wang, Jiahao Xun, Minjie Hong, Jieming Zhu, Tao Jin, Wang Lin, Haoyuan Li, Linjun Li, Yan Xia, Zhou Zhao, Zhenhua Dong |
| 2024 | KDD | Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time. | Haiyuan Zhao, Guohao Cai, Jieming Zhu, Zhenhua Dong, Jun Xu, Ji-Rong Wen |
| 2024 | PAKDD | Multi-sourced Integrated Ranking with Exposure Fairness. | Yifan Liu, Weiwen Liu, Wei Xia, Jieming Zhu, Weinan Zhang, Zhenhua Dong, Yang Wang, Ruiming Tang, Rui Zhang, Yong Yu |
| 2024 | RecSys | A Tutorial on Feature Interpretation in Recommender Systems. | Zhaocheng Du, Chuhan Wu, Qinglin Jia, Jieming Zhu, Xu Chen |
| 2024 | RecSys | Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models. | Yunjia Xi, Weiwen Liu, Jianghao Lin, Xiaoling Cai, Hong Zhu, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Yong Yu |
| 2024 | RecSys | Enhancing News Recommendation with Real-Time Feedback and Generative Sequence Modeling. | Qi Zhang, Jieming Zhu, Jiansheng Sun, Guohao Cai, Ruining Yu, Bangzheng He, Liangbi Li |
| 2024 | RecSys | CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation. | Jieming Zhu, Mengqun Jin, Qijiong Liu, Zexuan Qiu, Zhenhua Dong, Xiu Li |
| 2024 | WWW | LightCS: Selecting Quadratic Feature Crosses in Linear Complexity. | Zhaocheng Du, Junhao Chen, Qinglin Jia, Chuhan Wu, Jieming Zhu, Zhenhua Dong, Ruiming Tang |
| 2024 | WWW | 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, Yong Yu |
| 2024 | WWW | Discrete Semantic Tokenization for Deep CTR Prediction. | Qijiong Liu, Hengchang Hu, Jiahao Wu, Jieming Zhu, Min-Yen Kan, Xiao-Ming Wu |
| 2024 | WWW | 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 |
| 2024 | WWW | Benchmarking News Recommendation in the Era of Green AI. | Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiao-Ming Wu |
| 2024 | WWW | RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction. | Yushen Li, Jinpeng Wang, Tao Dai, Jieming Zhu, Jun Yuan, Rui Zhang, Shu-Tao Xia |
| 2024 | WWW | PMG : Personalized Multimodal Generation with Large Language Models. | Xiaoteng Shen, Rui Zhang, Xiaoyan Zhao, Jieming Zhu, Xi Xiao |
| 2024 | WWW | MART: Learning Hierarchical Music Audio Representations with Part-Whole Transformer. | Dong Yao, Jieming Zhu, Jiahao Xun, Shengyu Zhang, Zhou Zhao, Liqun Deng, Wenqiao Zhang, Zhenhua Dong, Xin Jiang |
| 2024 | WWW | Multimodal Pretraining and Generation for Recommendation: A Tutorial. | Jieming Zhu, Xin Zhou, Chuhan Wu, Rui Zhang, Zhenhua Dong |
| 2023 | AAAI | FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction. | Kelong Mao, Jieming Zhu, Liangcai Su, Guohao Cai, Yuru Li, Zhenhua Dong |
| 2023 | ISSRE | Loghub: A Large Collection of System Log Datasets for AI-driven Log Analytics. | Jieming Zhu, Shilin He, Pinjia He, Jinyang Liu, Michael R. Lyu |
| 2023 | KDD | ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop. | Jieming Zhu, Guohao Cai, Junjie Huang, Zhenhua Dong, Ruiming Tang, Weinan Zhang |
| 2023 | RecSys | Data-free Knowledge Distillation for Reusing Recommendation Models. | Cheng Wang, Jiacheng Sun, Zhenhua Dong, Jieming Zhu, Zhenguo Li, Ruixuan Li, Rui Zhang |
| 2023 | WWW | FANS: Fast Non-Autoregressive Sequence Generation for Item List Continuation. | Qijiong Liu, Jieming Zhu, Jiahao Wu, Tiandeng Wu, Zhenhua Dong, Xiao-Ming Wu |
| 2023 | SIGIR | Beyond Two-Tower Matching: Learning Sparse Retrievable Cross-Interactions for Recommendation. | Liangcai Su, Fan Yan, Jieming Zhu, Xi Xiao, Haoyi Duan, Zhou Zhao, Zhenhua Dong, Ruiming Tang |
| 2023 | SIGIR | DisCover: Disentangled Music Representation Learning for Cover Song Identification. | Jiahao Xun, Shengyu Zhang, Yanting Yang, Jieming Zhu, Liqun Deng, Zhou Zhao, Zhenhua Dong, Ruiqi Li, Lichao Zhang, Fei Wu |
| 2023 | SIGIR | FINAL: Factorized Interaction Layer for CTR Prediction. | Jieming Zhu, Qinglin Jia, Guohao Cai, Quanyu Dai, Jingjie Li, Zhenhua Dong, Ruiming Tang, Rui Zhang |
| 2022 | ACL | MINER: Multi-Interest Matching Network for News Recommendation. | Jian Li, Jieming Zhu, Qiwei Bi, Guohao Cai, Lifeng Shang, Zhenhua Dong, Xin Jiang, Qun Liu |
| 2022 | CIKM | LCD: Adaptive Label Correction for Denoising Music Recommendation. | Quanyu Dai, Yalei Lv, Jieming Zhu, Junjie Ye, Zhenhua Dong, Rui Zhang, Shu-Tao Xia, Ruiming Tang |
| 2022 | COLING | Boosting Deep CTR Prediction with a Plug-and-Play Pre-trainer for News Recommendation. | Qijiong Liu, Jieming Zhu, Quanyu Dai, Xiaoming Wu |
| 2022 | CVPR | Wnet: Audio-Guided Video Object Segmentation via Wavelet-Based Cross- Modal Denoising Networks. | Wenwen Pan, Haonan Shi, Zhou Zhao, Jieming Zhu, Xiuqiang He, Zhigeng Pan, Lianli Gao, Jun Yu, Fei Wu, Qi Tian |
| 2022 | WWW | PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation. | Yi Li, Jieming Zhu, Weiwen Liu, Liangcai Su, Guohao Cai, Qi Zhang, Ruiming Tang, Xi Xiao, Xiuqiang He |
| 2022 | WWW | Contrastive Learning with Positive-Negative Frame Mask for Music Representation. | Dong Yao, Zhou Zhao, Shengyu Zhang, Jieming Zhu, Yudong Zhu, Rui Zhang, Xiuqiang He |
| 2022 | SIGIR | ReLoop: A Self-Correction Continual Learning Loop for Recommender Systems. | Guohao Cai, Jieming Zhu, Quanyu Dai, Zhenhua Dong, Xiuqiang He, Ruiming Tang, Rui Zhang |
| 2022 | SIGIR | Multi-Level Interaction Reranking with User Behavior History. | Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu |
| 2022 | SIGIR | BARS: Towards Open Benchmarking for Recommender Systems. | Jieming Zhu, Quanyu Dai, Liangcai Su, Rong Ma, Jinyang Liu, Guohao Cai, Xi Xiao, Rui Zhang |
| 2021 | AAAI | Modeling High-order Interactions across Multi-interests for Micro-video Reommendation (Student Abstract). | Dong Yao, Shengyu Zhang, Zhou Zhao, Wenyan Fan, Jieming Zhu, Xiuqiang He, Fei Wu |
| 2021 | CIKM | SimpleX: A Simple and Strong Baseline for Collaborative Filtering. | Kelong Mao, Jieming Zhu, Jinpeng Wang, Quanyu Dai, Zhenhua Dong, Xi Xiao, Xiuqiang He |
| 2021 | CIKM | UltraGCN: Ultra Simplification of Graph Convolutional Networks for Recommendation. | Kelong Mao, Jieming Zhu, Xi Xiao, Biao Lu, Zhaowei Wang, Xiuqiang He |
| 2021 | CIKM | Open Benchmarking for Click-Through Rate Prediction. | Jieming Zhu, Jinyang Liu, Shuai Yang, Qi Zhang, Xiuqiang He |
| 2021 | IJCAI | UNBERT: User-News Matching BERT for News Recommendation. | Qi Zhang, Jingjie Li, Qinglin Jia, Chuyuan Wang, Jieming Zhu, Zhaowei Wang, Xiuqiang He |
| 2021 | SIGIR | RMBERT: News Recommendation via Recurrent Reasoning Memory Network over BERT. | Qinglin Jia, Jingjie Li, Qi Zhang, Xiuqiang He, Jieming Zhu |
| 2021 | SIGIR | Hierarchical Cross-Modal Graph Consistency Learning for Video-Text Retrieval. | Weike Jin, Zhou Zhao, Pengcheng Zhang, Jieming Zhu, Xiuqiang He, Yueting Zhuang |
| 2021 | SIGIR | Cross-Batch Negative Sampling for Training Two-Tower Recommenders. | Jinpeng Wang, Jieming Zhu, Xiuqiang He |
| 2020 | CIKM | Ensembled CTR Prediction via Knowledge Distillation. | Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng |
| 2020 | ECAI | Directional Adversarial Training for Recommender Systems. | Yangjun Xu, Liang Chen, Fenfang Xie, Weibo Hu, Jieming Zhu, Chuan Chen, Zibin Zheng |
| 2020 | SIGIR | Item Tagging for Information Retrieval: A Tripartite Graph Neural Network based Approach. | Kelong Mao, Xi Xiao, Jieming Zhu, Biao Lu, Ruiming Tang, Xiuqiang He |
| 2019 | ICSE | Tools and benchmarks for automated log parsing. | Jieming Zhu, Shilin He, Jinyang Liu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu |
| 2018 | APSEC | Detecting Duplicate Bug Reports with Convolutional Neural Networks. | Qi Xie, Zhiyuan Wen, Jieming Zhu, Cuiyun Gao, Zibin Zheng |
| 2017 | ICSE | IntelliAd: assisting mobile app developers in measuring ad costs automatically. | Cuiyun Gao, Yichuan Man, Hui Xu, Jieming Zhu, Yangfan Zhou, Michael R. Lyu |
| 2017 | ICWS | Drain: An Online Log Parsing Approach with Fixed Depth Tree. | Pinjia He, Jieming Zhu, Zibin Zheng, Michael R. Lyu |
| 2017 | ICWS | CARP: Context-Aware Reliability Prediction of Black-Box Web Services. | Jieming Zhu, Pinjia He, Qi Xie, Zibin Zheng, Michael R. Lyu |
| 2017 | QRS | Software Defect Prediction via Convolutional Neural Network. | Jian Li, Pinjia He, Jieming Zhu, Michael R. Lyu |
| 2016 | DSN | An Evaluation Study on Log Parsing and Its Use in Log Mining. | Pinjia He, Jieming Zhu, Shilin He, Jian Li, Michael R. Lyu |
| 2016 | ICWS | Asymmetric Correlation Regularized Matrix Factorization for Web Service Recommendation. | Qi Xie, Shenglin Zhao, Zibin Zheng, Jieming Zhu, Michael R. Lyu |
| 2016 | ISSRE | Experience Report: System Log Analysis for Anomaly Detection. | Shilin He, Jieming Zhu, Pinjia He, Michael R. Lyu |
| 2015 | ICSE | Learning to Log: Helping Developers Make Informed Logging Decisions. | Jieming Zhu, Pinjia He, Qiang Fu, Hongyu Zhang, Michael R. Lyu, Dongmei Zhang |
| 2015 | ICWS | A Privacy-Preserving QoS Prediction Framework for Web Service Recommendation. | Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu |
| 2015 | ISSRE | PAID: Prioritizing app issues for developers by tracking user reviews over versions. | Cuiyun Gao, Baoxiang Wang, Pinjia He, Jieming Zhu, Yangfan Zhou, Michael R. Lyu |
| 2014 | ICDCS | Towards Online, Accurate, and Scalable QoS Prediction for Runtime Service Adaptation. | Jieming Zhu, Pinjia He, Zibin Zheng, Michael R. Lyu |
| 2014 | ICSE | Where do developers log? an empirical study on logging practices in industry. | Qiang Fu, Jieming Zhu, Wenlu Hu, Jian-Guang Lou, Rui Ding, Qingwei Lin, Dongmei Zhang, Tao Xie |
| 2014 | ICWS | Location-Based Hierarchical Matrix Factorization for Web Service Recommendation. | Pinjia He, Jieming Zhu, Zibin Zheng, Jianlong Xu, Michael R. Lyu |
| 2013 | BigData | Service-Generated Big Data and Big Data-as-a-Service: An Overview. | Zibin Zheng, Jieming Zhu, Michael R. Lyu |
| 2012 | ICWS | WSP: A Network Coordinate Based Web Service Positioning Framework for Response Time Prediction. | Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu |
| 2012 | ISORC | A Clustering-Based QoS Prediction Approach for Web Service Recommendation. | Jieming Zhu, Yu Kang, Zibin Zheng, Michael R. Lyu |
| 1992 | AAAI | Operational Definition Refinement: A Discovery Process. | Jan M. Zytkow, Jieming Zhu, Robert Zembowicz |
| 1992 | ICML | The First Phase of Real-World Discovery: Determining Repeatability and Error of Experiments. | Jan M. Zytkow, Jieming Zhu, Robert Zembowicz |
| 1990 | AAAI | Automated Discovery in a Chemistry Laboratory. | Jan M. Zytkow, Jieming Zhu, Abul Hussam |