Jiancan Wu

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 46

Top Topics

Unstructured Data

Top Venues

Publications

Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, Xiangnan He
LLaRA: Large Language-Recommendation Assistant. SIGIR (2024)
Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He
Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients. CoRR (2024)
Yongduo Sui, Wenyu Mao, Shuyao Wang, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua
Enhancing Out-of-distribution Generalization on Graphs via Causal Attention Learning. ACM Trans. Knowl. Discov. Data 18 (5) (2024)
Chengpeng Li, Zheng Yuan, Hongyi Yuan, Guanting Dong, Keming Lu, Jiancan Wu, Chuanqi Tan, Xiang Wang, Chang Zhou
MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning. ACL (1) (2024)
Yuyue Zhao, Jiancan Wu, Xiang Wang, Wei Tang, Dingxian Wang, Maarten de Rijke
Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning. CoRR (2024)
Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jiawei Chen, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization. CoRR (2024)
Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation. WSDM (2024)
Chen-Lu Ding, Jiancan Wu, Wei Lin, Shiyang Shen, Xiang Wang, Yancheng Yuan
Adaptive Self-supervised Robust Clustering for Unstructured Data with Unknown Cluster Number. CoRR (2024)
Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He
Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients. SIGIR (2024)
Yanchen Luo, Sihang Li, Yongduo Sui, Junkang Wu, Jiancan Wu, Xiang Wang
Masked Graph Modeling with Multi- View Contrast. ICDE (2024)
Wenyu Mao, Jiancan Wu, Weijian Chen, Chongming Gao, Xiang Wang, Xiangnan He
Reinforced Prompt Personalization for Recommendation with Large Language Models. CoRR (2024)
Weizhi Nie, Xin Wen, Jing Liu, Jiawei Chen, Jiancan Wu, Guoqing Jin, Jing Lu, An-An Liu
Knowledge-Enhanced Causal Reinforcement Learning Model for Interactive Recommendation. IEEE Trans. Multim. 26 (2024)
Junkang Wu, Yuexiang Xie, Zhengyi Yang, Jiancan Wu, Jinyang Gao, Bolin Ding, Xiang Wang, Xiangnan He
β-DPO: Direct Preference Optimization with Dynamic β. CoRR (2024)
Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation. CoRR (2024)
Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang
BSL: Understanding and Improving Softmax Loss for Recommendation. ICDE (2024)
Yuyue Zhao, Jiancan Wu, Xiang Wang, Wei Tang, Dingxian Wang, Maarten de Rijke
Let Me Do It For You: Towards LLM Empowered Recommendation via Tool Learning. SIGIR (2024)
Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He
How graph convolutions amplify popularity bias for recommendation? Frontiers Comput. Sci. 18 (5) (2024)
Meishan Liu, Meng Jian, Yulong Bai, Jiancan Wu, Lifang Wu
Graph Contrastive Learning With Negative Propagation for Recommendation. IEEE Trans. Comput. Soc. Syst. 11 (3) (2024)
Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu
On the Effectiveness of Sampled Softmax Loss for Item Recommendation. ACM Trans. Inf. Syst. 42 (4) (2024)
Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He
Understanding Contrastive Learning via Distributionally Robust Optimization. CoRR (2023)
Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He
Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. NeurIPS (2023)
Chengpeng Li, Zhengyi Yang, Jizhi Zhang, Jiancan Wu, Dingxian Wang, Xiangnan He, Xiang Wang
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation. CoRR (2023)
Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He
GIF: A General Graph Unlearning Strategy via Influence Function. CoRR (2023)
Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He
Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion. CoRR (2023)
Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He
Large Language Model Can Interpret Latent Space of Sequential Recommender. CoRR (2023)
Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift. NeurIPS (2023)
Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He
GIF: A General Graph Unlearning Strategy via Influence Function. WWW (2023)
Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang
A Generic Learning Framework for Sequential Recommendation with Distribution Shifts. SIGIR (2023)
Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He
Understanding Contrastive Learning via Distributionally Robust Optimization. NeurIPS (2023)
Yang Zhang, Zhiyu Hu, Yimeng Bai, Fuli Feng, Jiancan Wu, Qifan Wang, Xiangnan He
Recommendation Unlearning via Influence Function. CoRR (2023)
Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang
BSL: Understanding and Improving Softmax Loss for Recommendation. CoRR (2023)
Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He
How Graph Convolutions Amplify Popularity Bias for Recommendation? CoRR (2023)
Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang, Xiangnan He
LLaRA: Aligning Large Language Models with Sequential Recommenders. CoRR (2023)
Chengpeng Li, Zheng Yuan, Hongyi Yuan, Guanting Dong, Keming Lu, Jiancan Wu, Chuanqi Tan, Xiang Wang, Chang Zhou
Query and Response Augmentation Cannot Help Out-of-domain Math Reasoning Generalization. CoRR (2023)
Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He
Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation. WWW (2023)
Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He
Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation. CoRR (2023)
Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang
Cross Pairwise Ranking for Unbiased Item Recommendation. CoRR (2022)
Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie
Graph convolution machine for context-aware recommender system. Frontiers Comput. Sci. 16 (6) (2022)
Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang
Cross Pairwise Ranking for Unbiased Item Recommendation. WWW (2022)
Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua
Causal Attention for Interpretable and Generalizable Graph Classification. KDD (2022)
Yongduo Sui, Xiang Wang, Jiancan Wu, An Zhang, Xiangnan He
Adversarial Causal Augmentation for Graph Covariate Shift. CoRR (2022)
Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu, Xiangnan He
On the Effectiveness of Sampled Softmax Loss for Item Recommendation. CoRR (2022)
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie
Self-supervised Graph Learning for Recommendation. SIGIR (2021)
Yongduo Sui, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua
Deconfounded Training for Graph Neural Networks. CoRR (2021)
Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie, Yongdong Zhang
Graph Convolution Machine for Context-aware Recommender System. CoRR (2020)
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie
Self-supervised Graph Learning for Recommendation. CoRR (2020)