Publications

Tongtian Zhu, WenhaoLi, Can Wang, FengxiangHe (2025). DICE: Data Influence Cascade in Decentralized Learning. In ICLR 2025.

Zhe Wang, ShengZhou, Jiawei Chen, ZhenZhang, BinbinHu, Yan Feng, Chun Chen, Can Wang (2025). Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding. In WSDM 2025.

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Shen Han, Zhiyao Zhou, Jiawei Chen, Yan Feng, Can Wang (2025). Uncertainty-Aware Graph Structure Learning. In WWW.

Shengjia Zhang, Jiawei Chen, Changdong Li, ShengZhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang (2024). Advancing Loss Functions in Recommender Systems: A Comparative Study with a Rényi Divergence-Based Solution. In AAAI 2025.

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Yichen Liu, Jiawei Chen, Yan Feng, Can Wang (2024). Confidence-aware Self-Semantic Distillation on Knowledge Graph Embedding. In CIKM.

Yu Cui, FengLiu, PengboWang, Bohao Wang, Heng Tang, YiWan, JunWang, Jiawei Chen (2024). Distillation Matters: Empowering Sequential Recommenders to Match the Performance of Large Language Models. In RecSys 2024.

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Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen, SiweiLyu (2024). Simple and Fast Distillation of Diffusion Models. In NeurIPS 2024.

Weiqin Yang, Jiawei Chen, Yan Feng, Chun Chen, Can Wang (2024). PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation. In NeurIPS 2024.

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Zeyu Wang, Qihao Shi, Jiawei Chen, Can Wang, MingliSong, XinyuWang (2024). Fast Query Answering by Labeling Index on Uncertain Graphs. In ICDE.

Sirui Chen, Jiawei Chen, ShengZhou, Bohao Wang, Shen Han, Can Wang (2024). SIGformer: Sign-aware Graph Transformer for Recommendation. In SIGIR 2024.

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Zhezheng Hao, HaonanXin, LongWei, LiaoyuanTang, RongWang, FeipingNie (2024). Towards expansive and adaptive hard negative mining: Graph contrastive learning via subspace preserving. In WWW 2024.

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Defang Chen, Zhenyu Zhou, Can Wang, ChunhuaShen, SiweiLyu (2024). On the Trajectory Regularity of ODE-based Diffusion Sampling. In ICML 2024.

Can Wang, Zhe Wang, Defang Chen, ShengZhou, Yan Feng, Chun Chen (2024). Online Adversarial Knowledge Distillation for Graph Neural Networks. In ESA 2024.

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Zhenyu Zhou, Defang Chen, Can Wang, Chun Chen (2024). Fast Ode-based Sampling for Diffusion Models in Around 5 Steps. In CVPR 2024.

Junkang Wu, Jiawei Chen, Jiancan Wu, Wentao Shi, Xiang Wang, Xiangnan He (2024). Understanding Contrastive Learning via Distributionally Robust Optimization. In NIPS 2023.

BinbinHu, WeifanWang, ShuhanWang, ZiqiLiu, BinShen, YongHe, Jiawei Chen (2024). The Devil is in the Sources! Knowledge Enhanced Cross-Domain Recommendation in an Information Bottleneck Perspective. In CIKM 2024.

ChangxinTian, BinbinHu, ChunjingGan, HaoyuChen, ZhuoZhang, LiYu, ZiqiLiu, ZhiqiangZhang, JunZhou, Jiawei Chen (2024). ReLand: Integrating Large Language Models' Insights into Industrial Recommenders via a Controllable Reasoning Pool. In Recsys 2024.

Siyi Lin, ShengZhou, Jiawei Chen, Yan Feng, Qihao Shi, Chun Chen, YingLi, Can Wang (2024). ReCRec: Reasoning the Causes of Implicit Feedback for Debiased Recommendation. In TOIS 2024.

JiancanWu, XiangWang, XingyuGao, Jiawei Chen, HongchengFu, TianyuQiu (2024). On the Effectiveness of Sampled Softmax Loss for Item Recommendation. In TOIS.

Bohao Wang, Feng Liu, Jiawei Chen, Xingyu Lou, Changwang Zhang, Jun Wang, Yuegang Sun, Yan Feng, Chun Chen, Can Wang (2024). MSL: Not All Tokens Are What You Need for Tuning LLM as a Recommender. In SIGIR 2025.

JiajiaChen, JiancanWu, Jiawei Chen, XinXin, YongLi, XiangnanHe (2024). How graph convolutions amplify popularity bias for recommendation?. FCS.

Siyi Lin, ChongmingGao, Jiawei Chen, ShengZhou, BinbinHu, Yan Feng, Chun Chen, Can Wang (2024). How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective. In TOIS 2024.

YuanqingYu, ChongmingGao, Jiawei Chen, Heng Tang, YuefengSun, QianChen, WeizhiMa, MinZhang (2024). How Do Recommendation Models Amplify Popularity Bias? An Analysis from the Spectral Perspective. In SIGIR 2024.

Ming Gu, Gaoming Yang, ShengZhou, Ning Ma, Jiawei Chen, Qiaoyu Tan, Meihan Liu, Jiajun Bu (2024). Homophily-enhanced Structure Learning for Graph Clustering. In CIKM 23.

Bohao Wang, Jiawei Chen, Changdong Li, ShengZhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang (2024). Distributionally Robust Graph-based Recommendation System. In WWW 2024.

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ZijieSong, Jiawei Chen, ShengZhou, Qihao Shi, Yan Feng, Chun Chen, Can Wang (2024). CDR: Conservative Doubly Robust Learning for Debiased Recommendation. In CIKM 23.

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JunkangWu, Jiawei Chen, JiancanWu, WentaoShi, JizhiZhang, XiangWang (2024). BSL: Understanding and Improving Softmax Loss for Recommendation. In ICDE 2024.

Zhiyao Zhou, Jiawei Chen, Yan Feng, Can Wang (2023). OpenGSL: A Comprehensive Benchmark for Graph Structure Learning. In NeurIPS.

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Wujie Sun, Defang Chen, Can Wang, DeshiYe, Yan Feng, Chun Chen (2023). Holistic Weighted Distillation for Semantic Segmentation. In ICME 2023.

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ShiyaLuo, Defang Chen, Can Wang (2023). Customizing Synthetic Data for Data-Free Student Learning. In ICME 2023.

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HailinZhang, Defang Chen, Can Wang (2023). Adaptive Multi-Teacher Knowledge Distillation with Meta-Learning. In ICME 2023.

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Wujie Sun, Defang Chen, Can Wang, DeshiYe, Yan Feng, Chun Chen (2023). Accelerating Diffusion Sampling with Classifier-based Feature Distillation. In ICME 2023.

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JiongyuGuo, Defang Chen, Can Wang (2023). Online Cross-Layer Knowledge Distillation on Graph Neural Networks with Deep Supervision. In NCA 2023.

ShiyaLuo, Defang Chen, Can Wang (2023). Knowledge Distillation with Deep Supervision. In IJCNN 2023.

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Zhezheng Hao, ZhouminLu, GuoxuLi, FeipingNie, RongWang, XuelongLi (2023). Ensemble clustering with attentional representation. TKDE 2023.

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JiongyuGuo, Defang Chen, Can Wang (2022). Alignahead: Online Cross-Layer Knowledge Extraction on Graph Neural Networks. In IJCNN 2022.

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Defang Chen, JianpingMei, HailinZhang, Can Wang, Yan Feng, Chun Chen (2022). Knowledge Distillation with the Reused Teacher Classifier. In CVPR 2022.

Can Wang, ShengZhou, KangYu, Defang Chen, BolangLi, Yan Feng, Chun Chen (2022). Collaborative Knowledge Distillation for Heterogeneous Information Network Embedding. In WWW 2022.

HailinZhang, Defang Chen, Can Wang (2022). Confidence-Aware Multi-Teacher Knowledge Distillation. In ICASSP 2022.

ZheHuiZhou, Can Wang, Yan Feng, Defang Chen (2022). JointE: Jointly Utilizing 1D And 2D Convolution for Knowledge Graph Embedding. In KBS 2022.

ShengZhou, YuchengWang, Defang Chen, Jiawei Chen, XinWang, Can Wang, JiajunBu (2022). Distilling Holistic Knowledge with Graph Neural Networks. In ICCV 2021.

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Defang Chen, JianpingMei, YuanZhang, Can Wang, Zhe Wang, Yan Feng, Chun Chen (2021). Cross-Layer Distillation with Semantic Calibration. In AAAI 2021.

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Defang Chen, JianpingMei, Can Wang, Yan Feng, Chun Chen (2020). Online Knowledge Distillation with Diverse Peers. In AAAI 2020.