Jiancan Wu

According to our database, Jiancan Wu authored at least 26 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

How graph convolutions amplify popularity bias for recommendation?

Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He

Frontiers Comput. Sci., October, 2024

Knowledge-Enhanced Causal Reinforcement Learning Model for Interactive Recommendation.

Weizhi Nie, Xin Wen, Jing Liu, Jiawei Chen, Jiancan Wu, Guoqing Jin, Jing Lu, An-An Liu

IEEE Trans. Multim., 2024

Leave No Patient Behind: Enhancing Medication Recommendation for Rare Disease Patients.

Zihao Zhao, Yi Jing, Fuli Feng, Jiancan Wu, Chongming Gao, Xiangnan He

CoRR, 2024

Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation.

Shuyao Wang, Yongduo Sui, Jiancan Wu, Zhi Zheng, Hui Xiong

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

BSL: Understanding and Improving Softmax Loss for Recommendation.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Jizhi Zhang, Xiang Wang

CoRR, 2023

LLaRA: Aligning Large Language Models with Sequential Recommenders.

Jiayi Liao, Sihang Li, Zhengyi Yang, Jiancan Wu, Yancheng Yuan, Xiang Wang

CoRR, 2023

Large Language Model Can Interpret Latent Space of Sequential Recommender.

Zhengyi Yang, Jiancan Wu, Yanchen Luo, Jizhi Zhang, Yancheng Yuan, An Zhang, Xiang Wang, Xiangnan He

CoRR, 2023

Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation.

Chengpeng Li, Zhengyi Yang, Jizhi Zhang, Jiancan Wu, Dingxian Wang, Xiangnan He, Xiang Wang

CoRR, 2023

Query and Response Augmentation Cannot Help Out-of-domain Math Reasoning Generalization.

Chengpeng Li, Zheng Yuan, Hongyi Yuan, Guanting Dong, Keming Lu, Jiancan Wu, Chuanqi Tan, Xiang Wang, Chang Zhou

CoRR, 2023

Recommendation Unlearning via Influence Function.

Yang Zhang, Zhiyu Hu, Yimeng Bai, Fuli Feng, Jiancan Wu, Qifan Wang, Xiangnan He

CoRR, 2023

How Graph Convolutions Amplify Popularity Bias for Recommendation?

Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He

CoRR, 2023

Adap-tau: Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Sheng Zhou, Xuezhi Cao, Xiangnan He

CoRR, 2023

GIF: A General Graph Unlearning Strategy via Influence Function.

Jiancan Wu, Yi Yang, Yuchun Qian, Yongduo Sui, Xiang Wang, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

Adap-τ : Adaptively Modulating Embedding Magnitude for Recommendation.

Jiawei Chen, Junkang Wu, Jiancan Wu, Xuezhi Cao, Sheng Zhou, Xiangnan He

Proceedings of the ACM Web Conference 2023, 2023

A Generic Learning Framework for Sequential Recommendation with Distribution Shifts.

Zhengyi Yang, Xiangnan He, Jizhi Zhang, Jiancan Wu, Xin Xin, Jiawei Chen, Xiang Wang

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion.

Zhengyi Yang, Jiancan Wu, Zhicai Wang, Xiang Wang, Yancheng Yuan, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding Contrastive Learning via Distributionally Robust Optimization.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift.

Yongduo Sui, Qitian Wu, Jiancan Wu, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang, Xiangnan He

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Graph convolution machine for context-aware recommender system.

Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie

Frontiers Comput. Sci., 2022

Adversarial Causal Augmentation for Graph Covariate Shift.

Yongduo Sui, Xiang Wang, Jiancan Wu, An Zhang, Xiangnan He

CoRR, 2022

On the Effectiveness of Sampled Softmax Loss for Item Recommendation.

Jiancan Wu, Xiang Wang, Xingyu Gao, Jiawei Chen, Hongcheng Fu, Tianyu Qiu, Xiangnan He

CoRR, 2022

Cross Pairwise Ranking for Unbiased Item Recommendation.

Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo, Ruiming Tang

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Causal Attention for Interpretable and Generalizable Graph Classification.

Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021

Deconfounded Training for Graph Neural Networks.

Yongduo Sui, Xiang Wang, Jiancan Wu, Xiangnan He, Tat-Seng Chua

CoRR, 2021

Self-supervised Graph Learning for Recommendation.

Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie

Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

2020

Graph Convolution Machine for Context-aware Recommender System.

Jiancan Wu, Xiangnan He, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian, Xing Xie, Yongdong Zhang

CoRR, 2020