Zhengyu Chen

According to our database, Zhengyu Chen authored at least 39 papers between 2019 and 2024.

Collaborative distances:

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

2024

Transferring Causal Mechanism over Meta-representations for Target-Unknown Cross-domain Recommendation.

Shengyu Zhang, Qiaowei Miao, Ping Nie, Mengze Li, Zhengyu Chen, Fuli Feng, Kun Kuang, Fei Wu

ACM Trans. Inf. Syst., July, 2024

Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace.

Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu

CoRR, 2024

Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts.

Jinluan Yang, Zhengyu Chen, Teng Xiao, Wenqiao Zhang, Yong Lin, Kun Kuang

CoRR, 2024

Discovering Invariant Neighborhood Patterns for Heterophilic Graphs.

Ruihao Zhang, Zhengyu Chen, Teng Xiao, Yueyang Wang, Kun Kuang

CoRR, 2024

Intelligent Model Update Strategy for Sequential Recommendation.

Zheqi Lv, Wenqiao Zhang, Zhengyu Chen, Shengyu Zhang, Kun Kuang

Proceedings of the ACM on Web Conference 2024, 2024

Let Models Speak Ciphers: Multiagent Debate through Embeddings.

Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Pareto Graph Self-Supervised Learning.

Zhengyu Chen, Teng Xiao, Donglin Wang, Min Zhang

Proceedings of the IEEE International Conference on Acoustics, 2024

Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models.

Siqi Wang, Zhengyu Chen, Bei Li, Keqing He, Min Zhang, Jingang Wang

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning.

Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Robust Heterophily Graph Learning via Uniformity Augmentation.

Xusheng Yang, Zhengyu Chen, Yuexian Zou

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

Learning to Reweight for Generalizable Graph Neural Network.

Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Learning to Reweight for Graph Neural Network.

Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu

CoRR, 2023

IDEAL: Toward High-efficiency Device-Cloud Collaborative and Dynamic Recommendation System.

Zheqi Lv, Zhengyu Chen, Shengyu Zhang, Kun Kuang, Wenqiao Zhang, Mengze Li, Beng Chin Ooi, Fei Wu

CoRR, 2023

DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization.

Zheqi Lv, Wenqiao Zhang, Shengyu Zhang, Kun Kuang, Feng Wang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Beng Chin Ooi, Fei Wu

Proceedings of the ACM Web Conference 2023, 2023

Simple and Asymmetric Graph Contrastive Learning without Augmentations.

Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang

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

Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective.

Teng Xiao, Zhengyu Chen, Suhang Wang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Invariant Graph Neural Network for Out-of-Distribution Nodes.

Zhengyu Chen, Yishu Gong, Liangliang Yang, Jianyu Zhang, Wei Zhang, Sihong He, Xusheng Zhang

Proceedings of the 15th International Conference on Machine Learning and Computing, 2023

Multi-Level Correlation Network For Few-Shot Image Classification.

Yunkai Dang, Meijun Sun, Min Zhang, Zhengyu Chen, Xinliang Zhang, Zheng Wang, Donglin Wang

Proceedings of the IEEE International Conference on Multimedia and Expo, 2023

MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters.

Min Zhang, Junkun Yuan, Yue He, Wenbin Li, Zhengyu Chen, Kun Kuang

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022

MetaNetwork: A Task-agnostic Network Parameters Generation Framework for Improving Device Model Generalization.

Zheqi Lv, Feng Wang, Kun Kuang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Fei Wu

CoRR, 2022

Knowledge Distillation of Transformer-based Language Models Revisited.

Chengqiang Lu, Jianwei Zhang, Yunfei Chu, Zhengyu Chen, Jingren Zhou, Fei Wu, Haiqing Chen, Hongxia Yang

CoRR, 2022

Towards Bridging Algorithm and Theory for Unbiased Recommendation.

Teng Xiao, Zhengyu Chen, Suhang Wang

CoRR, 2022

Decoupled Self-supervised Learning for Non-Homophilous Graphs.

Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

CoRR, 2022

Decoupled Self-supervised Learning for Graphs.

Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

End-to-End Open-Set Semi-Supervised Node Classification with Out-of-Distribution Detection.

Tiancheng Huang, Donglin Wang, Yuan Fang, Zhengyu Chen

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

The Role of Deconfounding in Meta-learning.

Yinjie Jiang, Zhengyu Chen, Kun Kuang, Luotian Yuan, Xinhai Ye, Zhihua Wang, Fei Wu, Ying Wei

Proceedings of the International Conference on Machine Learning, 2022

BA-GNN: On Learning Bias-Aware Graph Neural Network.

Zhengyu Chen, Teng Xiao, Kun Kuang

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Representation Matters When Learning From Biased Feedback in Recommendation.

Teng Xiao, Zhengyu Chen, Suhang Wang

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning.

Jinxin Liu, Donglin Wang, Qiangxing Tian, Zhengyu Chen

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Learning How to Propagate Messages in Graph Neural Networks.

Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Multi-Modal Meta Continual Learning.

Sibo Gai, Zhengyu Chen, Donglin Wang

Proceedings of the International Joint Conference on Neural Networks, 2021

Adaptive Adversarial Training for Meta Reinforcement Learning.

Shiqi Chen, Zhengyu Chen, Donglin Wang

Proceedings of the International Joint Conference on Neural Networks, 2021

Multi-Initialization Meta-Learning with Domain Adaptation.

Zhengyu Chen, Donglin Wang

Proceedings of the IEEE International Conference on Acoustics, 2021

Improving Cold-Start Recommendation via Multi-prior Meta-learning.

Zhengyu Chen, Donglin Wang, Shiqian Yin

Proceedings of the Advances in Information Retrieval, 2021

Pareto Self-Supervised Training for Few-Shot Learning.

Zhengyu Chen, Jixie Ge, Heshen Zhan, Siteng Huang, Donglin Wang

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems.

Zhengyu Chen, Ziqing Xu, Donglin Wang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Global and Local Tensor Factorization for Multi-criteria Recommender System.

Shuliang Wang, Jingting Yang, Zhengyu Chen, Hanning Yuan, Jing Geng, Zhen Hai

Patterns, 2020

2019

Deep Transfer Collaborative Filtering for Recommender Systems.

Sibo Gai, Feng Zhao, Yachen Kang, Zhengyu Chen, Donglin Wang, Ao Tang

Proceedings of the PRICAI 2019: Trends in Artificial Intelligence, 2019

Deep Tensor Factorization for Multi-Criteria Recommender Systems.

Zhengyu Chen, Sibo Gai, Donglin Wang

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019