News
20 Oct 2023
One paper is accepted by WSDM 2024 about label learning for short-video recommendation.
21 Sep 2023
I received RecSys 2023 Outstanding Reviewer Award.
6 Aug 2023
One paper is accepted by CIKM 2023 about label debiasing for recommendation.
27 July 2023
One co-authored paper is accepted by IEEE TBD about Uncertainty-aware Recommendation.
28 June 2023
Two co-authored short papers are accepted by RecSys 2023 about LLM for Recommendation.
5 April 2023
One full paper, one short paper and one DC paper have been accepted by SIGIR 2023 on invariant learning and abductive reasoning for recommendation.
26 Feb 2023
One paper is accepted by ICDE 2023 on invariant learning for loan default prediction.
30 July 2022
One paper is accepted by ACM TOIS on causal recommendation.
14 July 2021
Our SIGIR'21 paper "Causal Intervention for Leveraging Popularity Bias in Recommendation" receives Best Paper Honorable Mention.
16 April 2021
One first-author full paper is accepted by SIGIR, on causal inference for popularity bias in recsys. Thanks for my advisor and other co-authors!
23 April 2020
One first-author full paper is accepted by SIGIR, on meta-learning for recsys. Thanks for all co-authors!
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Yang Zhang
PhD Student
School of Information Science and Technology • GitHub • Google Scholar
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I am currently in the final year of my PhD program at Lab for Data Science, USTC, with a research focus on Recommender Systems. More specifically, my research centers on enhancing the reliability and trustworthiness of recommender systems, addressing critical challenges such as debiasing, temporal out-of-distribution (OOD) generalization, fairness, and privacy, primarily through a causal perspective. Currently, I am also actively involved in research that harnesses Large Language Models (LLMs) to empower recommender systems. I have authored over ten publications that have been featured in renowned conferences and journals like SIGIR, CIKM, and TOIS. Notably, my research on causal debiasing earned the distinction of Best Paper Honorable Mention at SIGIR 2021. Moreover, I have served as as the Program Committee (PC) member and reviewer for esteemed conferences and journals, including TOIS, TKDE, TIST, TKDD, TNNLS, WSDM, SIGIR, RecSys, SIGKDD, AAAI, etc.
Education
| University of Sicence and Technology of China (USTC) PhD student in Information and Communication Engineering Sep 2019 - Now, Hefei, China Advisor: Prof. Xiangnan He Mentor: Prof. Fuli Feng |
| University of Sicence and Technology of China (USTC) Bachelor in Electroic Information Engineering Sep 2015 - June 2019, Hefei, China |
Experiences
| Research Intern, Wechat, Tencent (Shen Zhen), July 2020 - July 2021 Mentor: Dr. Chonggang song (Wechat, Tencent) |
Tutorials & Workshop
| Large Language Models for Recommendation: Progresses and Future Directions
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He SIGIR-AP 2023 web page |
| The 1st Workshop on Recommendation with Generative Models
Wenjie Wang, Yong Liu, Yang Zhang, Weiwen Liu, Fuli Feng, Xiangnan He, Aixin Sun CIKM 2023 web page |
| Causal Recommendation: Progresses and Future Directions
Wenjie Wang, Yang Zhang, Haoxuan Li, Peng Wu, Fuli Feng, Xiangnan He SIGIR 2023 web page |
| Causal Recommendation: Progresses and Future Directions
Yang Zhang, Wenjie Wang, Peng Wu, Fuli Feng, Xiangnan He WWW 2022 web page |
Preprints
| CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation
Yang Zhang, Fuli Feng, Jizhi Zhang, Keqin Bao, Qifan Wang and Xiangnan He ArXiv 2023. pdf Codes |
| Recommendation Unlearning via Influence Function
Yang Zhang, Zhiyu Hu, Yimeng Bai, Fuli Feng, Jiancan Wu, Qifan Wang, Xiangnan He ArXiv 2023. pdf |
| Mitigating Hidden Confounding Effects for Causal Recommendation
Xinyuan Zhu, Yang Zhang, Fuli Feng, Xun Yang, Dingxian Wang, Xiangnan He submit to TKDE (major revison) pdf |
Publications
| LabelCraft: Empowering Short Video Recommendations with Automated Label Crafting
Yimeng Bai, Yang Zhang*, Jing Lu, Jianxin Chang, Xiaoxue Zang, Yanan Niu, Yang Song and Fuli Feng* WSDM 2024 (Poster, Accept rate: 18%). pdf Codes *Corresponding |
| Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework
Yang Zhang*, Yimeng Bai*, Jianxin Chang*, Xiaoxue Zang, Song Lu, Jing Lu, Fuli Feng, Yanan Niu, Yang Song CIKM 2023 (Applied Research Paper, Accept rate: 32%). pdf |
| Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation
Yang Zhang*, Tianhao Shi*, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He and Yongdong Zhang SIGIR 2023 (Full, Accept rate: 20%) pdf Codes |
| Causal Intervention for Leveraging Popularity Bias in Recommendation
Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling & Yongdong Zhang SIGIR 2021 (Full, Accept rate: 21%) pdf Codes; Best Paper Honorable Mention |
| How to Retrain Recommender System? A Sequential Meta-Learning Approach
Yang Zhang, Fuli Feng, Chenxu Wang, Xiangnan He, Meng Wang, Yan Li & Yongdong Zhang SIGIR 2020 (Full, Accept rate: 26%) pdf Codes |
| Addressing Confounding Feature Issue for Causal Recommendation
Xiangnan He, Yang Zhang*, Fuli Feng, Chonggang Song, Lingling Yi, Guohui Ling & Yongdong Zhang ACM TOIS 2023 pdf Codes *Corresponding |
| Prediction then Correction: An Abductive Prediction Correction Method for Sequential Recommendation
Yulong Huang*, Yang Zhang*, Qifan Wang, Chenxu Wang and Fuli Feng SIGIR 2023 (short, Accept rate: 25%) pdf Codes *Equal contribution |
| LightMIRM: Light Meta-learned Invariant Risk Minimization for Trustworthy Loan Default Prediction
Meng Jiang, Yang Zhang, Yuan Gao, Yansong Wang, Fuli Feng and Xiangnan He ICDE 2023 (Industry and Applications Track) pdf Codes |
| Rethinking Missing Data: Aleatoric Uncertainty-Aware Recommendation
Chenxu Wang, Fuli Feng, Yang Zhang, Qifan Wang, Xunhan Hu, Xiangnan He IEEE TBD 2023; pdf |
| TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He RecSys 2023 (Short). pdf |
| Is ChatGPT Fair for Recommendation? Evaluating Fairness in Large Language Model Recommendation
Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Fuli Feng, Xiangnan He RecSys 2023 (Short). pdf |
| Mitigating Spurious Correlations for Self-supervised Recommendation
Xinyu Lin, Yiyan Xu, Wenjie Wang, Yang Zhang and Fuli Feng Machine Intelligence Research (2023) pdf Codes |
| Towards Trustworthy Recommender System: A Faithful and Responsible Recommendation Perspective
Yang Zhang SIGIR 2023 (Doctoral Consortium) pdf |
Services & Awards & Patents
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Invited Reviewer for ACM TOIS, IEEE TKDE, IEEE TNNLS, ACM TIST and ACM TKDD |
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Program committee member of WWW 2024, SIGIR 2023, KDD 2023, RecSys 2023, WSDM (2023,2024), AAAI (2023,2024), SIGIR-AP (2023), ECML/PKDD 2022 |
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RecSys 2023 Outstanding Reviewer Award, 2023
- ACM RecSys |
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National Scholarship, 2021
- USTC, China |
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SIGIR Best Paper Honorable Mention, 2021
- ACM SIGIR |
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National Scholarship, 2018
- USTC, China |
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National Encouragement Scholarship, 2017
- USTC, China |
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Outstanding Student Scholarship, 2016&2017
- USTC, China |
Useful Links
| Prof. Xiangnan He | Causality Reading List | Causal Recommendation Tutorial | |
Last update: June 28, 2023. Webpage template borrows from prof. Xiangnan He.