Zhengyu Chen - RankMe

68 papers A* 22A 3B 2Misc 3Journal 32Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling. AAAI Zhengyu Chen, Yudong Wang, Teng Xiao, Ruochen Zhou, Xuesheng Yang, Wei Wang, Zhifang Sui, Jingang Wang
2026	A*	`conf`	Scaling and Transferability of Annealing Strategies in Large Language Model Training. AAAI Siqi Wang, Zhengyu Chen, Teng Xiao, Zheqi Lv, Jinluan Yang, Xunliang Cai, Jingang Wang, Xiaomeng Li
2026	J	`jnl`	SkillCraft: Can LLM Agents Learn to Use Tools Skillfully? CoRR Shiqi Chen, Jingze Gai, Ruochen Zhou, Jinghan Zhang, Tongyao Zhu, Junlong Li, Kangrui Wang, Zihan Wang, Zhengyu Chen, Klara Kaleb, Ning Miao, Siyang Gao, Cong Lu, Manling Li, Junxian He, Yee Whye Teh
2026	J	`jnl`	TopoCurate:Modeling Interaction Topology for Tool-Use Agent Training. CoRR Jinluan Yang, Yuxin Liu, Zhengyu Chen, Chengcheng Han, Yueqing Sun, Qi Gu, Hui Su, Xunliang Cai, Fei Wu, Kun Kuang
2025	J	`jnl`	Can Tool-Integrated Reinforcement Learning Generalize Across Diverse Domains? CoRR Zhengyu Chen, Jinluan Yang, Teng Xiao, Ruochen Zhou, Luan Zhang, Xiangyu Xi, Xiaowei Shi, Wei Wang, Jinggang Wang
2025	J	`jnl`	Does Learning Mathematical Problem-Solving Generalize to Broader Reasoning? CoRR Ruochen Zhou, Minrui Xu, Shiqi Chen, Junteng Liu, Yunqi Li, Xinxin Lin, Zhengyu Chen, Junxian He
2025	—	`conf`	Explaining Length Bias in LLM-Based Preference Evaluations. EMNLP (Findings) Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, Tianfu Wang, Zhengyu Chen, Nicholas Jing Yuan, Jianxun Lian, Kaize Ding, Hui Xiong
2025	J	`jnl`	From Mathematical Reasoning to Code: Generalization of Process Reward Models in Test-Time Scaling. CoRR Zhengyu Chen, Yudong Wang, Teng Xiao, Ruochen Zhou, Xuesheng Yang, Wei Wang, Zhifang Sui, Jingang Wang
2025	A*	`conf`	Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts. WWW Jinluan Yang, Zhengyu Chen, Teng Xiao, Yong Lin, Wenqiao Zhang, Kun Kuang
2025	A*	`conf`	Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace. ICLR Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu
2025	J	`jnl`	Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging. CoRR Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang
2025	A*	`conf`	On a Connection Between Imitation Learning and RLHF. ICLR Teng Xiao, Yige Yuan, Mingxiao Li, Zhengyu Chen, Vasant G. Honavar
2025	J	`jnl`	On a Connection Between Imitation Learning and RLHF. CoRR Teng Xiao, Yige Yuan, Mingxiao Li, Zhengyu Chen, Vasant G. Honavar
2025	—	`conf`	Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies. ACL (1) Zhengyu Chen, Siqi Wang, Teng Xiao, Yudong Wang, Shiqi Chen, Xunliang Cai, Junxian He, Jingang Wang
2025	J	`jnl`	Scaling and Transferability of Annealing Strategies in Large Language Model Training. CoRR Siqi Wang, Zhengyu Chen, Teng Xiao, Zheqi Lv, Jinluan Yang, Xunliang Cai, Jingang Wang, Xiaomeng Li
2025	A*	`conf`	SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. ICLR Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G. Honavar
2025	J	`jnl`	SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters. CoRR Teng Xiao, Yige Yuan, Zhengyu Chen, Mingxiao Li, Shangsong Liang, Zhaochun Ren, Vasant G. Honavar
2025	J	`jnl`	Simple Denoising Diffusion Language Models. CoRR Huaisheng Zhu, Zhengyu Chen, Shijie Zhou, Zhihui Xie, Yige Yuan, Zhimeng Guo, Siyuan Xu, Hangfan Zhang, Vasant G. Honavar, Teng Xiao
2025	J	`jnl`	Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs. CoRR Zhengyu Chen, Siqi Wang, Teng Xiao, Yudong Wang, Shiqi Chen, Xunliang Cai, Junxian He, Jingang Wang
2025	J	`jnl`	Unifying Adversarial Perturbation for Graph Neural Networks. CoRR Jinluan Yang, Ruihao Zhang, Zhengyu Chen, Fei Wu, Kun Kuang
2024	J	`jnl`	Discovering Invariant Neighborhood Patterns for Heterophilic Graphs. CoRR Ruihao Zhang, Zhengyu Chen, Teng Xiao, Yueyang Wang, Kun Kuang
2024	A*	`conf`	Intelligent Model Update Strategy for Sequential Recommendation. WWW Zheqi Lv, Wenqiao Zhang, Zhengyu Chen, Shengyu Zhang, Kun Kuang
2024	A*	`conf`	Learning to Reweight for Generalizable Graph Neural Network. AAAI Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu
2024	A*	`conf`	Let Models Speak Ciphers: Multiagent Debate through Embeddings. ICLR Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang
2024	—	`conf`	Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning. EMNLP (Findings) Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding
2024	J	`jnl`	Let's Ask GNN: Empowering Large Language Model for Graph In-Context Learning. CoRR Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding
2024	J	`jnl`	Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts. CoRR Jinluan Yang, Zhengyu Chen, Teng Xiao, Wenqiao Zhang, Yong Lin, Kun Kuang
2024	J	`jnl`	Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace. CoRR Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu
2024	J	`jnl`	Multi-Level Correlation Network For Few-Shot Image Classification. CoRR Yunkai Dang, Min Zhang, Zhengyu Chen, Xinliang Zhang, Zheng Wang, Meijun Sun, Donglin Wang
2024	Misc	`conf`	Pareto Graph Self-Supervised Learning. ICASSP Zhengyu Chen, Teng Xiao, Donglin Wang, Min Zhang
2024	A	`conf`	Robust Heterophily Graph Learning via Uniformity Augmentation. CIKM Xusheng Yang, Zhengyu Chen, Yuexian Zou
2024	A*	`conf`	Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models. EMNLP Siqi Wang, Zhengyu Chen, Bei Li, Keqing He, Min Zhang, Jingang Wang
2024	J	`jnl`	Scaling Laws Across Model Architectures: A Comparative Analysis of Dense and MoE Models in Large Language Models. CoRR Siqi Wang, Zhengyu Chen, Bei Li, Keqing He, Min Zhang, Jingang Wang
2024	J	`jnl`	Transferring Causal Mechanism over Meta-representations for Target-Unknown Cross-domain Recommendation. ACM Trans. Inf. Syst. Shengyu Zhang, Qiaowei Miao, Ping Nie, Mengze Li, Zhengyu Chen, Fuli Feng, Kun Kuang, Fei Wu
2023	A*	`conf`	DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization. WWW Zheqi Lv, Wenqiao Zhang, Shengyu Zhang, Kun Kuang, Feng Wang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Beng Chin Ooi, Fei Wu
2023	J	`jnl`	IDEAL: Toward High-efficiency Device-Cloud Collaborative and Dynamic Recommendation System. CoRR Zheqi Lv, Zhengyu Chen, Shengyu Zhang, Kun Kuang, Wenqiao Zhang, Mengze Li, Beng Chin Ooi, Fei Wu
2023	Misc	`conf`	Invariant Graph Neural Network for Out-of-Distribution Nodes. ICMLC Zhengyu Chen, Yishu Gong, Liangliang Yang, Jianyu Zhang, Wei Zhang, Sihong He, Xusheng Zhang
2023	J	`jnl`	Learning How to Propagate Messages in Graph Neural Networks. CoRR Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang
2023	J	`jnl`	Learning to Reweight for Graph Neural Network. CoRR Zhengyu Chen, Teng Xiao, Kun Kuang, Zheqi Lv, Min Zhang, Jinluan Yang, Chengqiang Lu, Hongxia Yang, Fei Wu
2023	J	`jnl`	Let Models Speak Ciphers: Multiagent Debate through Embeddings. CoRR Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang
2023	A*	`conf`	MAP: Towards Balanced Generalization of IID and OOD through Model-Agnostic Adapters. ICCV Min Zhang, Junkun Yuan, Yue He, Wenbin Li, Zhengyu Chen, Kun Kuang
2023	A	`conf`	Multi-Level Correlation Network For Few-Shot Image Classification. ICME Yunkai Dang, Meijun Sun, Min Zhang, Zhengyu Chen, Xinliang Zhang, Zheng Wang, Donglin Wang
2023	A*	`conf`	Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. KDD Teng Xiao, Zhengyu Chen, Suhang Wang
2023	A*	`conf`	Simple and Asymmetric Graph Contrastive Learning without Augmentations. NeurIPS Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang
2023	J	`jnl`	Simple and Asymmetric Graph Contrastive Learning without Augmentations. CoRR Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang
2022	A*	`conf`	BA-GNN: On Learning Bias-Aware Graph Neural Network. ICDE Zhengyu Chen, Teng Xiao, Kun Kuang
2022	A*	`conf`	Decoupled Self-supervised Learning for Graphs. NeurIPS Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang
2022	J	`jnl`	Decoupled Self-supervised Learning for Non-Homophilous Graphs. CoRR Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang
2022	A*	`conf`	End-to-End Open-Set Semi-Supervised Node Classification with Out-of-Distribution Detection. IJCAI Tiancheng Huang, Donglin Wang, Yuan Fang, Zhengyu Chen
2022	J	`jnl`	Knowledge Distillation of Transformer-based Language Models Revisited. CoRR Chengqiang Lu, Jianwei Zhang, Yunfei Chu, Zhengyu Chen, Jingren Zhou, Fei Wu, Haiqing Chen, Hongxia Yang
2022	A*	`conf`	Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning. AAAI Jinxin Liu, Donglin Wang, Qiangxing Tian, Zhengyu Chen
2022	J	`jnl`	MetaNetwork: A Task-agnostic Network Parameters Generation Framework for Improving Device Model Generalization. CoRR Zheqi Lv, Feng Wang, Kun Kuang, Yongwei Wang, Zhengyu Chen, Tao Shen, Hongxia Yang, Fei Wu
2022	A	`conf`	Representation Matters When Learning From Biased Feedback in Recommendation. CIKM Teng Xiao, Zhengyu Chen, Suhang Wang
2022	A*	`conf`	The Role of Deconfounding in Meta-learning. ICML Yinjie Jiang, Zhengyu Chen, Kun Kuang, Luotian Yuan, Xinhai Ye, Zhihua Wang, Fei Wu, Ying Wei
2022	J	`jnl`	Towards Bridging Algorithm and Theory for Unbiased Recommendation. CoRR Teng Xiao, Zhengyu Chen, Suhang Wang
2021	B	`conf`	Adaptive Adversarial Training for Meta Reinforcement Learning. IJCNN Shiqi Chen, Zhengyu Chen, Donglin Wang
2021	J	`jnl`	Adaptive Adversarial Training for Meta Reinforcement Learning. CoRR Shiqi Chen, Zhengyu Chen, Donglin Wang
2021	A*	`conf`	Deep Transfer Tensor Decomposition with Orthogonal Constraint for Recommender Systems. AAAI Zhengyu Chen, Ziqing Xu, Donglin Wang
2021	—	`conf`	Improving Cold-Start Recommendation via Multi-prior Meta-learning. ECIR (2) Zhengyu Chen, Donglin Wang, Shiqian Yin
2021	J	`jnl`	Learn Goal-Conditioned Policy with Intrinsic Motivation for Deep Reinforcement Learning. CoRR Jinxin Liu, Donglin Wang, Qiangxing Tian, Zhengyu Chen
2021	A*	`conf`	Learning How to Propagate Messages in Graph Neural Networks. KDD Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang
2021	Misc	`conf`	Multi-Initialization Meta-Learning with Domain Adaptation. ICASSP Zhengyu Chen, Donglin Wang
2021	B	`conf`	Multi-Modal Meta Continual Learning. IJCNN Sibo Gai, Zhengyu Chen, Donglin Wang
2021	A*	`conf`	Pareto Self-Supervised Training for Few-Shot Learning. CVPR Zhengyu Chen, Jixie Ge, Heshen Zhan, Siteng Huang, Donglin Wang
2021	J	`jnl`	Pareto Self-Supervised Training for Few-Shot Learning. CoRR Zhengyu Chen, Jixie Ge, Heshen Zhan, Siteng Huang, Donglin Wang
2020	J	`jnl`	Global and Local Tensor Factorization for Multi-criteria Recommender System. Patterns Shuliang Wang, Jingting Yang, Zhengyu Chen, Hanning Yuan, Jing Geng, Zhen Hai
2019	—	`conf`	Deep Tensor Factorization for Multi-Criteria Recommender Systems. IEEE BigData Zhengyu Chen, Sibo Gai, Donglin Wang
2019	—	`conf`	Deep Transfer Collaborative Filtering for Recommender Systems. PRICAI (3) Sibo Gai, Feng Zhao, Yachen Kang, Zhengyu Chen, Donglin Wang, Ao Tang