Zun Wang

According to our database, Zun Wang authored at least 24 papers between 2021 and 2026.

Collaborative distances:

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

2026

Tokenizing 3D Molecule Structure with Quantized Spherical Coordinates.

Kaiyuan Gao, Yusong Wang, Haoxiang Guan, Zun Wang, Qizhi Pei, John E. Hopcroft, Kun He, Lijun Wu

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

2025

DGRO: Enhancing LLM Reasoning via Exploration-Exploitation Control and Reward Variance Management.

Xuerui Su, Liya Guo, Yue Wang, Yi Zhu, Zhiming Ma, Zun Wang, Yuting Liu

CoRR, May, 2025

Trust Region Preference Approximation: A simple and stable reinforcement learning algorithm for LLM reasoning.

Xuerui Su, Shufang Xie, Guoqing Liu, Yingce Xia, Renqian Luo, Peiran Jin, Zhiming Ma, Yue Wang, Zun Wang, Yuting Liu

CoRR, April, 2025

Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance.

Liya Guo, Zun Wang, Chang Liu, Junzhe Li, Pipi Hu, Yi Zhu

CoRR, March, 2025

UniGenX: Unified Generation of Sequence and Structure with Autoregressive Diffusion.

Gongbo Zhang, Yanting Li, Renqian Luo, Pipi Hu, Zeru Zhao, Lingbo Li, Guoqing Liu, Zun Wang, Ran Bi, Kaiyuan Gao, Liya Guo, Yu Xie, Chang Liu, Jia Zhang, Tian Xie, Robert Pinsler, Claudio Zeni, Ziheng Lu, Yingce Xia, Marwin H. S. Segler, Maik Riechert, Li Yuan, Lei Chen, Haiguang Liu, Tao Qin

CoRR, March, 2025

Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems.

Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Han Yang, Sam Harshe, Zun Wang, Chang Liu, Jia Zhang, Bin Shao, Mark B. Gerstein

CoRR, February, 2025

HybriDNA: A Hybrid Transformer-Mamba2 Long-Range DNA Language Model.

Mingqian Ma, Guoqing Liu, Chuan Cao, Pan Deng, Tri Dao, Albert Gu, Peiran Jin, Zhao Yang, Yingce Xia, Renqian Luo, Pipi Hu, Zun Wang, Yuan-Jyue Chen, Haiguang Liu, Tao Qin

CoRR, February, 2025

NatureLM: Deciphering the Language of Nature for Scientific Discovery.

Yingce Xia, Peiran Jin, Shufang Xie, Liang He, Chuan Cao, Renqian Luo, Guoqing Liu, Yue Wang, Zequn Liu, Yuan-Jyue Chen, Zekun Guo, Yeqi Bai, Pan Deng, Yaosen Min, Ziheng Lu, Hongxia Hao, Han Yang, Jielan Li, Chang Liu, Jia Zhang, Jianwei Zhu, Kehan Wu, Wei Zhang, Kaiyuan Gao, Qizhi Pei, Qian Wang, Xixian Liu, Yanting Li, Houtian Zhu, Yeqing Lu, Mingqian Ma, Zun Wang, Tian Xie, Krzysztof Maziarz, Marwin H. S. Segler, Zhao Yang, Zilong Chen, Yu Shi, Shuxin Zheng, Lijun Wu, Chen Hu, Peggy Dai, Tie-Yan Liu, Haiguang Liu, Tao Qin

CoRR, February, 2025

E2Former: A Linear-time Efficient and Equivariant Transformer for Scalable Molecular Modeling.

Yunyang Li, Lin Huang, Zhihao Ding, Chu Wang, Xinran Wei, Han Yang, Zun Wang, Chang Liu, Yu Shi, Peiran Jin, Jia Zhang, Mark Gerstein, Tao Qin

CoRR, January, 2025

SE3Set: Harnessing Equivariant Hypergraph Neural Networks for Molecular Representation Learning.

Hongfei Wu, Lijun Wu, Guoqing Liu, Zhirong Liu, Bin Shao, Zun Wang

Trans. Mach. Learn. Res., 2025

Potential Score Matching: Debiasing Molecular Structure Sampling with Potential Energy Guidance.

Liya Guo, Zun Wang, Chang Liu, Junzhe Li, Pipi Hu, Yi Zhu, Tao Qin

Trans. Mach. Learn. Res., 2025

Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity.

Erpai Luo, Xinran Wei, Lin Huang, Yunyang Li, Han Yang, Zaishuo Xia, Zun Wang, Chang Liu, Bin Shao, Jia Zhang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Enhancing the Scalability and Applicability of Kohn-Sham Hamiltonians for Molecular Systems.

Yunyang Li, Zaishuo Xia, Lin Huang, Xinran Wei, Samuel Harshe, Han Yang, Erpai Luo, Zun Wang, Jia Zhang, Chang Liu, Bin Shao, Mark Gerstein

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Author Correction: Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.

He Li, Zun Wang, Nianlong Zou, Meng Ye, Runzhang Xu, Xiaoxun Gong, Wenhui Duan, Yong Xu

Nat. Comput. Sci., November, 2024

Self-Consistency Training for Hamiltonian Prediction.

He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

CoRR, 2024

Leveraging Biomolecule and Natural Language through Multi-Modal Learning: A Survey.

Qizhi Pei, Lijun Wu, Kaiyuan Gao, Jinhua Zhu, Yue Wang, Zun Wang, Tao Qin, Rui Yan

CoRR, 2024

Infusing Self-Consistency into Density Functional Theory Hamiltonian Prediction via Deep Equilibrium Models.

Zun Wang, Chang Liu, Nianlong Zou, He Zhang, Xinran Wei, Lin Huang, Lijun Wu, Bin Shao

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction.

He Zhang, Chang Liu, Zun Wang, Xinran Wei, Siyuan Liu, Nanning Zheng, Bin Shao, Tie-Yan Liu

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Long-Short-Range Message-Passing: A Physics-Informed Framework to Capture Non-Local Interaction for Scalable Molecular Dynamics Simulation.

Yunyang Li, Yusong Wang, Lin Huang, Han Yang, Xinran Wei, Jia Zhang, Tong Wang, Zun Wang, Bin Shao, Tie-Yan Liu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Efficiently incorporating quintuple interactions into geometric deep learning force fields.

Zun Wang, Guoqing Liu, Yichi Zhou, Tong Wang, Bin Shao

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

2022

Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation.

He Li, Zun Wang, Nianlong Zou, Meng Ye, Runzhang Xu, Xiaoxun Gong, Wenhui Duan, Yong Xu

Nat. Comput. Sci., 2022

An ensemble of VisNet, Transformer-M, and pretraining models for molecular property prediction in OGB Large-Scale Challenge @ NeurIPS 2022.

Yusong Wang, Shaoning Li, Tong Wang, Zun Wang, Xinheng He, Bin Shao, Tie-Yan Liu

CoRR, 2022

2021

Heterogeneous relational message passing networks for molecular dynamics simulations.

Zun Wang, Chong Wang, Sibo Zhao, Yong Xu, Shaogang Hao, Chang Yu Hsieh, Bing-Lin Gu, Wenhui Duan

CoRR, 2021

Symmetry-adapted graph neural networks for constructing molecular dynamics force fields.

Zun Wang, Chong Wang, Sibo Zhao, Shiqiao Du, Yong Xu, Bing-Lin Gu, Wenhui Duan

CoRR, 2021