About Me: Weizhi Ma (马为之)

I am now a research assistant professor at the Institute for AI Industry Research (AIR), Tsinghua University. Before joining AIR, I was a Postdoctoral Research Fellow in THUIR group, Department of Computer Science and Technology in Tsinghua University, Beijing, China. My major research interests are in Recommender System, User Modeling, and Information Retrieval.

I got my PhD degree from Tsinghua University in 2019, supervised by Prof. Shaoping Ma, Prof. Min Zhang, and Prof. Yiqun Liu, I was a Visiting Research Fellow from Feb. 2018 to Jun. 2018 at INK Research Lab, University of Southern California, supervised by Prof. Xiang Ren. I have visited University College London for two month, supervised by Prof. Jun Wang and visited NExT Center for three month, supervised by Prof. Chua Tat-seng.

Recent Professional Activities

  • I serve as an assitant editor for ACM TOIS from July, 2020.
  • I serve as a web master for the virtual conference of SIGIR 2020.
  • I serve as SPC member of IJCAI 2021.
  • I serve as PC member of SIGIR 2018-, theWebConf 2020-, CIKM 2020-, COLING 2020-, WSDM 2021-, AAAI 2021-, KDD 2021-, EMNLP 2021-, etc.
  • I serve as a reviewer for TOIS, TKDE, TNNLS, FCS, TIST, JCST, etc.

Foundations

  • I am supported by Scholar of Young Talent Promoting Project of CAST in 2022.
  • I am funded by National Natural Science Foundation of China in 2020.
  • I am funded by China Postdoctoral Science Foundation in 2020.
  • I am supported by Shuimu Tsinghua Scholar Program in 2019.

Selected Publications

IN THE YEAR OF 2024:

  • Junkai Li, Siyu Wang, Meng Zhang, Weitao Li, Yunghwei Lai, Xinhui Kang, Weizhi Ma, Yang Liu. Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents. (arXiv)
  • Jiayin Wang, Weizhi Ma, Peijie Sun, Min Zhang, Jian-Yun Nie. Understanding User Experience in Large Language Model Interactions. (arXiv)
  • Jiayin Wang, Fengran Mo, Weizhi Ma, Peijie Sun, Min Zhang, Jian-Yun Nie. A User-Centric Benchmark for Evaluating Large Language Models. (arXiv)
  • Jiayu Li, Aixin Sun, Weizhi Ma, Peijie Sun, Min Zhang. Recommender for Its Purpose: Repeat and Exploration in Food Delivery Recommendations. (arXiv)
  • Zhiyu He, Jiayu Li, Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma. Introducing EEG Analyses to Help Personal Music Preference Prediction. (arXiv)
  • Weitao Li, Junkai Li, Weizhi Ma, Yang Liu. Citation-Enhanced Generation for LLM-based Chatbot. (ACL 2024)
  • Shenghao Yang, Weizhi Ma, Peijie Sun, Qingyao Ai, Yiqun Liu, Mingchen Cai, Min Zhang. Sequential Recommendation with Latent Relations based on Large Language Model. (SIGIR 2024)
  • Hanyu Li, Weizhi Ma, Peijie Sun, Jiayu Li, Cunxiang Yin, Yancheng He, Guoqiang Xu, Min Zhang, Shaoping Ma. Aiming at the Target: Filter Collaborative Information for Cross-Domain Recommendation. (SIGIR 2024)
  • Yuanqing Yu, Chongming Gao, Jiawei Chen, Heng Tang, Yuefeng Sun, Qian Chen, Weizhi Ma, Min Zhang. EasyRL4Rec: A User-Friendly Code Library for Reinforcement Learning Based Recommender Systems. (SIGIR 2024 Resource)
  • Zhefan Wang, Yuanqing Yu, Wendi Zheng, Weizhi Ma, Min Zhang. Multi-Agent Collaboration Framework for Recommender Systems. (SIGIR 2024 Demo)
  • Zhefan Wang, Weizhi Ma, Min Zhang. To Recommend or Not: Recommendability Identification in Conversations with Pre-trained Language Models. (DASFAA 2024)
  • Jiayu Li, Peijie Sun, Chumeng Jiang, Weizhi Ma, Qingyao Ai, Min Zhang. A Situation-aware Enhancer for Personalized Recommendation. (DASFAA 2024)
  • Shenghao Yang, Weizhi Ma, Peijie Sun, Min Zhang, Qingyao Ai, Yiqun Liu, Mingchen Cai. Common Sense Enhanced Knowledge-based Recommendation with Large Language Model. (DASSFA 2024)
  • Jimmy Lin, Junkai Li, Jiasi Gao, Weizhi Ma, Yang Liu. Jointly Modeling Spatio-Temporal Features of Tactile Signals for Action Classification. (AAAI 2024)
  • Yifan Wang, Peijie Sun, Weizhi Ma, Min Zhang, Yuan Zhang, Peng Jiang, Shaoping Ma. Intersectional Two-sided Fairness in Recommendation. (TheWebConf 2024)
  • Vadim Grigorev, Jiayu Li, Weizhi Ma, Zhiyu He, Min Zhang, Yiqun Liu, Ming Yan, Ji Zhang. SiTunes: A Situational Music Recommendation Dataset with Physiological and Psychological Signals. (CHIIR 2024)

IN THE YEAR OF 2023:

  • Shenghao Yang, Chenyang Wang, Yankai Liu, Kangping Xu, Weizhi Ma, Yiqun Liu, Min Zhang, Haitao Zeng, Junlan Feng, Chao Deng. Collaborative Word-based Pre-trained Item Representation for Transferable Recommendation. (ICDM 2023)
  • Chenyang Wang, Yankai Liu, Yuanqing Yu, Weizhi Ma, Min Zhang, Yiqun Liu, Haitao Zeng, Junlan Feng, Chao Deng. Two-sided Calibration for Quality-aware Responsible Recommendation. (RecSys 2023)
  • Qingyao Ai, Ting Bai, Zhao Cao, Yi Chang, Jiawei Chen, Zhumin Chen, Zhiyong Cheng, Shoubin Dong, Zhicheng Dou, Fuli Feng, Shen Gao, Jiafeng Guo, Xiangnan He, Yanyan Lan, Chenliang Li, Yiqun Liu, Ziyu Lyu, Weizhi Ma, Jun Ma, Zhaochun Ren, Pengjie Ren, Zhiqiang Wang, Mingwen Wang, Ji-Rong Wen, Le Wu, Xin Xin, Jun Xu, Dawei Yin, Peng Zhang, Fan Zhang, Weinan Zhang, Min Zhang, Xiaofei Zhu. Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community. (AI Open)
  • Hongyu Lu, Weizhi Ma, Yifan Wang, Min Zhang, Xiang Wang, Yiqun Liu, Tat-Seng Chua, Shaoping Ma. User Perception of Recommendation Explanation: Are Your Explanations What Users Need? (TOIS)
  • Yifan Wang, Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma. A survey on the fairness of recommender systems. (TOIS)
  • Junqi Zhang, Yiqun Liu, Jiaxin Mao, Weizhi Ma, Jiazheng Xu, Shaoping Ma, Qi Tian. User Behavior Simulation for Search Result Re-Ranking. (TOIS)
  • Jiayin Wang, Weizhi Ma, Chumeng Jiang, Min Zhang, Yuan Zhang, Biao Li, and Peng Jiang. Measuring Item Global Residual Value for Fair Recommendation. (SIGIR 2023)
  • Jiayu Li, Peijie Sun, Zhefan Wang, Weizhi Ma, Yangkun Li, Min Zhang, Zhoutian Feng, and Daiyue Xue. Intent-aware Ranking Ensemble for Personalized Recommendation. (SIGIR 2023)
  • Jiayu Li, Zhiyu He, Min Zhang, Weizhi Ma, Ye Jin, Lei Zhang, Shuyang Zhang, Yiqun Liu, Shaoping Ma. Estimating Rare Diseases Incidences with Large-scale Internet Search Data: Two-step Machine Learning Method. (JMIR Infodemiology)

IN THE YEAR OF 2022:

  • Mingze Sun, Weizhi Ma, Yang Liu. Global and Local Feature Interaction with Vision Transformer for Few-shot Image Classification. (CIKM 2022)
  • Yuancheng Sun, Yimeng Chen, Weizhi Ma, Wenhao Huang, Kang Liu, Zhiming Ma, Wei-Ying Ma, Yanyan Lan. PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction. (CIKM 2022)
  • Chenyang Wang, Zhefan Wang, Yankai Liu, Yang Ge, Weizhi Ma, Min Zhang, Yiqun Liu, Junlan Feng, Chao Deng and Shaoping Ma. Target Interest Distillation for Multi-Interest Recommendation. (CIKM 2022)
  • Yangkun Li, Weizhi Ma, Chong Chen, Min Zhang, Yiqun Liu, Shaoping Ma, Yuekui Yang. A Survey on Dropout Methods and Experimental Verification in Recommendation. (TKDE)
  • Jiayin Wang, Weizhi Ma, Jiayu Li, Hongyu Lu, Min Zhang, Biao Li, Yiqun Liu, Peng Jiang, Shaopin Ma. Make Fairness More Fair: Fair Item Utility Estimation and Exposure Re-Distribution. (KDD 2022)
  • Chenyang Wang, Yuanqing Yu, Weizhi Ma, Min Zhang, Chong Chen, Yiqun Liu, Shaoping Ma. Towards Representation Alignment and Uniformity in Collaborative Filtering. (KDD 2022)
  • Chenyang Wang, Weizhi Ma, Chong Chen, Min Zhang, Yiqun Liu, Shaoping Ma. Sequential Recommendation with Multiple Contrast Signals. (TOIS)
  • Chong Chen, Weizhi Ma, Min Zhang, Chenyang Wang, Yiqun Liu, Shaoping Ma. Revisiting Negative Sampling VS. Non-Sampling in Implicit Recommendation. (TOIS)
  • Xiangsheng Li, Jiaxin Mao, Weizhi Ma, Zhijing Wu, Yiqun Liu, Min Zhang, Shaoping Ma, Zhaowei Wang, Xiuqiang He. A Cooperative Neural Information Retrieval Pipeline with Knowledge Enhanced Automatic Query Reformulation. (WSDM 2022)

IN THE YEAR OF 2021:

  • Jun Yang, Weizhi Ma, Min Zhang, Xin Zhou, Yiqun Liu, Shaoping Ma. LegalGNN: Legal Information Enhanced Graph Neural Network for Recommendation. (TOIS)
  • Shaoyun Shi, Weizhi Ma, Zhen Wang, Min Zhang, Kun Fang, Jingfang Xu, Yiqun Liu and Shaoping Ma. WG4Rec: Modeling Textual Content with Word Graph for News Recommendation. (CIKM 2021)
  • Jia Chen, Yiqun Liu, Jiaxin Mao, Fan Zhang, Tetsuya Sakai, Weizhi Ma, Min Zhang and Shaoping Ma. Incorporating Query Reformulating Behavior into Web Search Evaluation. (CIKM 2021)
  • Jiayu Li, Weizhi Ma, Min Zhang, Pengyu Wang, Yiqun Liu and Shaoping Ma. Know Yourself: Physical and Psychological Self-Awareness With Lifelog. (Frontiers in Digital Health)
  • Jiayu Li, Hongyu Lu, Chenyang Wang, Weizhi Ma, Min Zhang, Xiangyu Zhao, Wei Qi, Yiqun Liu, Shaoping Ma. A Difficulty-Aware Framework for Churn Prediction and Intervention in Games. (KDD 2021)
  • Hongyu Lu, Weizhi Ma, Min Zhang, Maarten de Rijke, Yiqun Liu and Shaoping Ma. Standing in Your Shoes: External Assessments for Personalized Recommender Systems (SIGIR 2021)
  • Chong Chen, Weizhi Ma, Min Zhang, Zhaowei Wang, Xiuqiang He, Chenyang Wang, Yiqun Liu, Shaoping Ma. Graph Heterogeneous Multi-Relational Recommendation (AAAI 2021).
  • Chenyang Wang, Weizhi Ma, Min Zhang, Chuancheng Lv, Fengyuan Wan, Huijie Lin, Taoran Tang, Yiqun Liu and Shaoping Ma. Temporal Cross-Effects in Knowledge Tracing (WSDM 2021).
  • Xiangsheng Li, Jiaxin Mao, Weizhi Ma, Yiqun Liu, Min Zhang, Shaoping Ma, Zhaowei Wang and Xiuqiang He. Topic-enhanced knowledge-aware retrieval model for diverse relevance estimation (theWebConf 2021).
  • Jia Chen, Jiaxin Mao, Yiqun Liu, Ziyi Ye, Weizhi Ma, Chao Wang, Min Zhang, Shaoping Ma. A Hybrid Framework for Session Context Modeling (TOIS).
  • Xiangsheng Li, Maarten de Rijke, Yiqun Liu, Jiaxin Mao, Weizhi Ma, Min Zhang and Shaoping Ma. Investigating Session Search Behavior with Knowledge Graphs (SIGIR 2021, short paper)

IN THE YEAR OF 2020:

  • Chenyang Wang, Weizhi Ma, Min Zhang, Yiqun Liu and Shaoping Ma. Towards Dynamic User Intention: Temporal Evolution of Item Relations in Sequential Recommendation (TOIS).
  • Shaoyun Shi, Hanxiong Chen, Weizhi Ma, Jiaxin Mao, Min Zhang and Yongfeng Zhang. Neural Logic Reasoning (CIKM 2020).
  • Xiangsheng Li, Maarten de Rijke, Yiqun Liu, Jiaxin Mao, Weizhi Ma, Min Zhang and Shaoping Ma. Learning Better Representations for Neural Information Retrieval with Graph Information (CIKM 2020).
  • Shaoyun Shi, Weizhi Ma, Min Zhang, Yongfeng Zhang, Xinxing Yu, Houzhi Shan, Yiqun Liu and Shaoping Ma. Beyond User Embedding Matrix: Learning to Hash for Modeling Large-Scale Users in Recommendation (SIGIR 2020).
  • Chenyang Wang, Min Zhang, Weizhi Ma, Yiqun Liu and Shaoping Ma. Make It a CHORUS: Context- and Knowledge-aware Item Modeling for Recommendation (SIGIR 2020).
  • Chong Chen, Min Zhang, Weizhi Ma, Yiqun Liu and Shaoping Ma. Jointly Non-Sampling Learning for Knowledge Graph Enhanced Recommendation (SIGIR 2020).
  • Fan Zhang, Jiaxin Mao, Yiqun Liu, Weizhi Ma, Min Zhang and Shaoping Ma. Cascade or Recency: Constructing Better Evaluation Metrics for Session Search (SIGIR 2020).
  • Fan Zhang, Jiaxin Mao, Yiqun Liu, Xiaohui Xie, Weizhi Ma, Min Zhang and Shaoping Ma. Models Versus Satisfaction: Towards a Better Understanding of Evaluation Metrics (SIGIR 2020, Best paper honorable mention).
  • Yunqiu Shao, Jiaxin Mao, Yiqun Liu, Weizhi Ma Ken Satoh, Min Zhang, and Shaoping Ma. BERT-PLI: Modeling Paragraph-Level Interactions for Legal Case Retrieval (IJCAI 2020).
  • Chong Chen, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma. Efficient Non-Sampling Factorization Machines for Optimal Context-Aware Recommendation (theWebConf 2020).
  • Chong Chen, Min Zhang, Yongfeng Zhang, Weizhi Ma, Yiqun Liu, Shaoping Ma. Efficient Heterogeneous Collaborative Filtering without Negative Sampling for Recommendation (AAAI 2020).
  • Zhen Wang, Weizhi Ma, Min Zhang, Weipeng Chen, Jingfang Xu, Yiqun Liu, and Shaoping Ma. Incorporating Knowledge and Content Information to Boost News Recommendation (NLPCC 2020).
  • Bin Hao, Min Zhang, Weizhi Ma, Shaoyun Shi, Xinxing Yu, Houzhi Shan, Yiqun Liu, and Shaoping Ma. Negative Feedback Aware Hybrid Sequential Neural Recommendation Model (NLPCC 2020).

IN THE YEAR OF 2019:

  • Weizhi Ma, Min Zhang, Yue Cao, Woojeong Jin, Chenyang Wang, Yiqun Liu, Shaoping Ma, and Xiang Ren. Jointly Learning Explainable Rules for Recommendation with Knowledge Graph (theWebConf 2019).
  • Chenyang Wang, Min Zhang, Weizhi Ma, Yiqun Liu, and Shaoping Ma. Modeling Item-Specific Temporal Dynamics of Repeat Consumption for Recommender Systems (theWebConf 2019).
  • Hongyu Lu, Min Zhang, Weizhi Ma, Yunqiu Shao, Yiqun Liu, and Shaoping Ma. Quality Effects on User Preferences and Behaviors in Mobile News Streaming (theWebConf 2019).
  • Hongyu Lu, Min Zhang, Weizhi Ma, Ce Wang, Feng Xia, Yiqun Liu, Leyu Lin, and Shaoping Ma. Effects of User Negative Experience in Mobile News Streaming (SIGIR 2019).
  • Chong Chen, Min Zhang, Chenyang Wang, Weizhi Ma, Minming Li, Yiqun Liu, and Shaoping Ma. An Efficient Adaptive Transfer Neural Network for Social-aware Recommendation (SIGIR 2019).
  • Weizhi Ma, Zhen Wang, Min Zhang, Jing Qian, Huanbo Luan, Yiqun Liu, and Shaoping Ma. Stance Influences Your Thoughts: Psychology-Inspired Social Media Analytics (NLPCC 2019)

IN THE YEAR OF 2018 and Before:

  • Weizhi Ma, Min Zhang, Chenyang Wang, Cheng Luo, Yiqun Liu, and Shaoping Ma. Your Tweets Reveal What You Like: Introducing Cross-media Content Information into Multi-domain Recommendation (IJCAI 2018).
  • Bin Liu, Min Zhang, Weizhi Ma, Xin Li, Yiqun Liu, and Shaoping Ma. A Two- step Information Accumulation Strategy for Learning from Highly Imbalanced Data (CIKM 2017).
  • Min Zhang, Biyuan Ding, Weizhi Ma, Yunzhi Tan, Yiqun Liu, and Shaoping Ma. Hybrid recommendation approach enhanced by deep learning (Journal of Tsinghua University (Science and Technology)).
  • Weizhi Ma, Min Zhang, Yiqun Liu, and Shaoping Ma. Multi-Grained Role La- beling Based on Multi-Modality Information for Real Customer Service Telephone Conversation (IJCAI 2016).
  • Bin Hao, Min Zhang, Weizhi Ma, Jiashen Sun, Yiqun Liu, Shaoping Ma, Xuan Zhu, and Hengliang Luo. Finding the True Crowds: User Filtering in Microblogs (NLPCC 2016).
  • Weizhi Ma, Min Zhang, Yiqun Liu, Shaoping Ma, and Linfeng Chen. Beyond Your Interests: Exploring the Information Behind User Tags (NLPCC 2015).