Jiancan Wu is now a postdoc in LDS, Department of Electronic Engineering and Information Science(6系), University of Science and Technology of China. His research interests include information retrieval, data mining, self-supervised learning, particularly in recommender systems, graph learning.

Selected Publications

In the Year of 2024:

pdf	β-DPO: Direct Preference Optimization with Dynamic β Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu*, Jinyang Gao, Bolin Ding, Xiang Wang, and Xiangnan He NeurIPS 2024 (Accept Rate: 25.8%)    Codes   (*Corresponding)

pdf	Customizing Language Models with Instance-wise LoRA for Sequential Recommendation Xiaoyu Kong, Jiancan Wu*, An Zhang, Leheng Sheng, Hui Lin, Xiang Wang, and Xiangnan He NeurIPS 2024 (Accept Rate: 25.8%)   (*Corresponding)

pdf	Text-guided small molecule generation via diffusion model Yanchen Luo, Junfeng Fang, Sihang Li, Zhiyuan Liu, Jiancan Wu, An Zhang, Wenjie Du, and Xiang Wang iScience

pdf	Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning Yuyue Zhao, Jiancan Wu*, Xiang Wang, Wei Tang, Dingxian Wang, and Maarten de Rijke SIGIR 2024 (Full, Accept Rate: 20.1%)    Codes   (*Corresponding)

pdf	MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning Chengpeng Li, Zheng Yuan, Hongyi Yuan, Guanting Dong, Keming Lu, Jiancan Wu, Chuanqi Tan, Xiang Wang, and Chang Zhou ACL 2024 (Full, Accept Rate: 21.3%)

pdf	LLaRA: Large Language-Recommendation Assistant Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, and Xiangnan He SIGIR 2024 (Full, Accept Rate: 20.1%)    Codes

pdf	Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, and Xiangnan He SIGIR 2024 (Full, Accept Rate: 20.1%)    Codes

pdf	BSL: Understanding and Improving Softmax Loss for Recommendation Junkang Wu, Jiawei Chen, Jiancan Wu*, Wentao Shi, Jizhi Zhang, and Xiang Wang ICDE 2024 (Full)    Codes    (*Corresponding)

pdf	Masked Graph Modeling with Multi-View Contrast Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, and Xiang Wang ICDE 2024 (Full)    Codes

pdf	Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, and Hui Xiong WSDM 2024 (Full, Accept Rate: 18%)    Codes

pdf	On the Effectiveness of Sampled Softmax Loss for Item Recommendation Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, and Tianyu Qiu ACM Transactions on Information Systems (TOIS 2024)    Codes

pdf	Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang, Jiancan Wu, Xiangnan He, and Tat-Seng Chua ACM Transactions on Knowledge Discovery from Data (TKDD 2024)    Codes

In the Year of 2023:

pdf	Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion Zhengyi Yang, Jiancan Wu*, Zhicai Wang, Xiang Wang, Yancheng Yuan, and Xiangnan He NeurIPS 2023 (Poster, Accept Rate: 26.1%)    Codes    (*Corresponding)

pdf	Understanding Contrastive Learning via Distributionally Robust Optimization Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, and Xiangnan He NeurIPS 2023 (Poseter, Accept Rate: 26.1%)    Codes

pdf	Unleashing the Power of Graph Data Augmentation on Covariate Shift Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, and Xiangnan He NeurIPS 2023 (Poster, Accept Rate: 26.1%)    Codes

pdf	A Generic Learning Framework for Sequential Recommendation with Distribution Shifts Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, and Xiang Wang SIGIR 2023 (Full, Accept Rate: 20.1%)    Codes

pdf	GIF: A General Graph Unlearning Strategy via Influence Function Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, and Xiangnan He WWW 2023 (Full, Accept Rate: 19.2%)    Codes

pdf	Adap-τ: Adpatively Modulating Embedding Magnitude for Recommendation Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, and Xiangnan He WWW 2023 (Full, Accept Rate: 19.2%)    Codes

pdf	How graph convolutions amplify popularity bias for recommendation? Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He Frontiers of Computer Science (FCS 2023)    Codes

In the Year of 2022:

pdf	Graph Convolution Machine for Context-aware Recommender System Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, and Xing Xie Frontiers of Computer Science (FCS 2022)    Codes

pdf	Cross Pairwise Ranking for Unbiased Item Recommendation Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, and Ruiming Tang WWW 2022 (Full, Accept rate: 17.7%)    Codes

pdf	Causal Attention for Interpretable and Generalizable Graph Classification Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, and Tat-Seng Chua KDD 2022 (Full, Accept rate: 15.0%)    Codes

In the Year of 2021:

pdf	Self-supervised Graph Learning for Recommendation JiancanWu, XiangWang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, and Xing Xie. SIGIR 2021 (Full, Accept rate: 21%)   • arXiv    • Codes    • Slides

Experiences

Postdoc Research Fellow, University of Science and Technology of China, June 2022 - Present Advisor: Prof. Xiangnan He (LDS: Lab for Data Science)

Research Intern, Tencent Music Entertainment Group, Shenzhen, May 2021 - Sep 2021 Mentor: Norman Bai

Useful Links

Machine Learning Reading List

Deep Learning Reading List

Last update: Nov 2nd, 2024. Webpage template borrows from Xiangnan He.