Deep Tensor Factorization for Multi-Criteria Recommender Systems. - Zhengyu Chen 001; Sibo Gai; Donglin Wang (IEEE BigData, 2019)

Deep Transfer Collaborative Filtering for Recommender Systems. - Sibo Gai; Feng Zhao 014; Yachen Kang; Zhengyu Chen 001; Donglin Wang; Ao Tang (PRICAI (3), 2019)

Global and Local Tensor Factorization for Multi-criteria Recommender System. - Shuliang Wang 001; Jingting Yang; Zhengyu Chen 001; Hanning Yuan; Jing Geng; Zhen Hai (Patterns, 2020)

Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems. - Zhengyu Chen 001; Ziqing Xu; Donglin Wang (AAAI, 2021)

Pareto Self-Supervised Training for Few-Shot Learning. - Zhengyu Chen 001; Jixie Ge; Heshen Zhan; Siteng Huang; Donglin Wang (CVPR, 2021)

Improving Cold-Start Recommendation via Multi-prior Meta-learning. - Zhengyu Chen 001; Donglin Wang; Shiqian Yin (ECIR (2), 2021)

Multi-Initialization Meta-Learning with Domain Adaptation. - Zhengyu Chen 001; Donglin Wang (ICASSP, 2021)

Adaptive Adversarial Training for Meta Reinforcement Learning. - Shiqi Chen; Zhengyu Chen 001; Donglin Wang (IJCNN, 2021)

Multi-Modal Meta Continual Learning. - Sibo Gai; Zhengyu Chen 001; Donglin Wang (IJCNN, 2021)

Learning How to Propagate Messages in Graph Neural Networks. - Teng Xiao; Zhengyu Chen 001; Donglin Wang; Suhang Wang (KDD, 2021)

Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning. - Jinxin Liu; Donglin Wang; Qiangxing Tian; Zhengyu Chen 001 (AAAI, 2022)

Representation Matters When Learning From Biased Feedback in Recommendation. - Teng Xiao; Zhengyu Chen 001; Suhang Wang (CIKM, 2022)

BA-GNN: On Learning Bias-Aware Graph Neural Network. - Zhengyu Chen 001; Teng Xiao; Kun Kuang (ICDE, 2022)

The Role of Deconfounding in Meta-learning. - Yinjie Jiang; Zhengyu Chen 001; Kun Kuang; Luotian Yuan; Xinhai Ye; Zhihua Wang 008; Fei Wu 001; Ying Wei 001 (ICML, 2022)

End-to-End Open-Set Semi-Supervised Node Classification with Out-of-Distribution Detection. - Tiancheng Huang; Donglin Wang; Yuan Fang 001; Zhengyu Chen 001 (IJCAI, 2022)

Decoupled Self-supervised Learning for Graphs. - Teng Xiao; Zhengyu Chen 001; Zhimeng Guo; Zeyang Zhuang; Suhang Wang (NeurIPS, 2022)

Decoupled Self-supervised Learning for Non-Homophilous Graphs. - Teng Xiao; Zhengyu Chen 001; Zhimeng Guo; Zeyang Zhuang; Suhang Wang (CoRR, 2022)

Towards Bridging Algorithm and Theory for Unbiased Recommendation. - Teng Xiao; Zhengyu Chen 001; Suhang Wang (CoRR, 2022)

Knowledge Distillation of Transformer-based Language Models Revisited. - Chengqiang Lu; Jianwei Zhang 012; Yunfei Chu; Zhengyu Chen 001; Jingren Zhou 001; Fei Wu 001; Haiqing Chen; Hongxia Yang (CoRR, 2022)

MetaNetwork: A Task-agnostic Network Parameters Generation Framework for Improving Device Model Generalization. - Zheqi Lv; Feng Wang 072; Kun Kuang; Yongwei Wang; Zhengyu Chen 001; Tao Shen 002; Hongxia Yang; Fei Wu 001 (CoRR, 2022)

MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters. - Min Zhang 005; Junkun Yuan; Yue He; Wenbin Li; Zhengyu Chen 001; Kun Kuang (ICCV, 2023)

Multi-Level Correlation Network For Few-Shot Image Classification. - Yunkai Dang; Meijun Sun; Min Zhang 005; Zhengyu Chen 001; Xinliang Zhang; Zheng Wang 008; Donglin Wang (ICME, 2023)

Invariant Graph Neural Network for Out-of-Distribution Nodes. - Zhengyu Chen 001; Yishu Gong; Liangliang Yang; Jianyu Zhang; Wei Zhang; Sihong He; Xusheng Zhang (ICMLC, 2023)

Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. - Teng Xiao; Zhengyu Chen 001; Suhang Wang (KDD, 2023)

Simple and Asymmetric Graph Contrastive Learning without Augmentations. - Teng Xiao; Huaisheng Zhu; Zhengyu Chen 001; Suhang Wang (NeurIPS, 2023)

DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization. - Zheqi Lv; Wenqiao Zhang; Shengyu Zhang 001; Kun Kuang; Feng Wang 072; Yongwei Wang; Zhengyu Chen 001; Tao Shen 002; Hongxia Yang; Beng Chin Ooi; Fei Wu 001 (WWW, 2023)

IDEAL: Toward High-efficiency Device-Cloud Collaborative and Dynamic Recommendation System. - Zheqi Lv; Zhengyu Chen 001; Shengyu Zhang 001; Kun Kuang; Wenqiao Zhang; Mengze Li 001; Beng Chin Ooi; Fei Wu 001 (CoRR, 2023)

Learning to Reweight for Graph Neural Network. - Zhengyu Chen 001; Teng Xiao; Kun Kuang; Zheqi Lv; Min Zhang 005; Jinluan Yang; Chengqiang Lu; Hongxia Yang; Fei Wu 001 (CoRR, 2023)

Learning to Reweight for Generalizable Graph Neural Network. - Zhengyu Chen 001; Teng Xiao; Kun Kuang; Zheqi Lv; Min Zhang 005; Jinluan Yang; Chengqiang Lu; Hongxia Yang; Fei Wu 001 (AAAI, 2024)

Robust Heterophily Graph Learning via Uniformity Augmentation. - Xusheng Yang; Zhengyu Chen 001; Yuexian Zou (CIKM, 2024)

Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning. - Zhengyu Hu; Yichuan Li 001; Zhengyu Chen 001; Jingang Wang; Han Liu; Kyumin Lee; Kaize Ding (EMNLP (Findings), 2024)

Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models. - Siqi Wang; Zhengyu Chen 001; Bei Li; Keqing He 001; Min Zhang 005; Jingang Wang (EMNLP, 2024)

Pareto Graph Self-Supervised Learning. - Zhengyu Chen 001; Teng Xiao; Donglin Wang; Min Zhang 005 (ICASSP, 2024)

Let Models Speak Ciphers: Multiagent Debate through Embeddings. - Chau Pham 001; Boyi Liu 001; Yingxiang Yang; Zhengyu Chen 001; Tianyi Liu; Jianbo Yuan; Bryan A. Plummer; Zhaoran Wang 001; Hongxia Yang (ICLR, 2024)

Intelligent Model Update Strategy for Sequential Recommendation. - Zheqi Lv; Wenqiao Zhang; Zhengyu Chen 001; Shengyu Zhang 001; Kun Kuang (WWW, 2024)

Discovering Invariant Neighborhood Patterns for Heterophilic Graphs. - Ruihao Zhang; Zhengyu Chen 001; Teng Xiao; Yueyang Wang; Kun Kuang (CoRR, 2024)

Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace. - Jinluan Yang; Anke Tang; Didi Zhu; Zhengyu Chen 001; Li Shen 008; Fei Wu 001 (CoRR, 2024)

Transferring Causal Mechanism over Meta-representations for Target-Unknown Cross-domain Recommendation. - Shengyu Zhang 001; Qiaowei Miao; Ping Nie; Mengze Li 001; Zhengyu Chen 001; Fuli Feng; Kun Kuang; Fei Wu 001 (ACM Trans. Inf. Syst., 2024)

Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies. - Zhengyu Chen 001; Siqi Wang; Teng Xiao; Yudong Wang; Shiqi Chen; Xunliang Cai; Junxian He; Jingang Wang (ACL (1), 2025)

SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. - Teng Xiao; Yige Yuan; Zhengyu Chen 001; Mingxiao Li 004; Shangsong Liang; Zhaochun Ren; Vasant G. Honavar (ICLR, 2025)

On a Connection Between Imitation Learning and RLHF. - Teng Xiao; Yige Yuan; Mingxiao Li 004; Zhengyu Chen 001; Vasant G. Honavar (ICLR, 2025)

Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts. - Jinluan Yang; Zhengyu Chen 001; Teng Xiao; Yong Lin; Wenqiao Zhang; Kun Kuang (WWW, 2025)

Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging. - Jinluan Yang; Dingnan Jin; Anke Tang; Li Shen 008; Didi Zhu; Zhengyu Chen 001; Daixin Wang; Qing Cui; Zhiqiang Zhang 012; Jun Zhou 011; Fei Wu 001; Kun Kuang (CoRR, 2025)

From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling. - Zhengyu Chen 001; Yudong Wang; Teng Xiao; Ruochen Zhou; Xuesheng Yang; Wei Wang; Zhifang Sui; Jingang Wang (CoRR, 2025)

Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning? - Ruochen Zhou; Minrui Xu; Shiqi Chen; Junteng Liu; Yunqi Li; Xinxin Lin; Zhengyu Chen 001; Junxian He (CoRR, 2025)

Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs. - Zhengyu Chen 001; Siqi Wang; Teng Xiao; Yudong Wang; Shiqi Chen; Xunliang Cai; Junxian He; Jingang Wang (CoRR, 2025)