@article{cheng2026gpflow,title={Variable-Length Generative Protein Design via Generalized Poisson Flow},author={Cheng*, Chaoran and Ni*, Zhanghan and Qu*, Yanru and Chen, Yuxin and Guo, Ruihan and Fan, Jiajun and Liu, Ge},journal={arXiv preprint arXiv:2607.09039},year={2026},}
A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion
Chaoran Cheng*, Jiaqi Guan*, Milong Ren, Chengyue Gong, Cong Liu, Xinshi Chen, Ge Liu, and Wenzhi Xiao
title = {{A-CODE}: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion},author = {Cheng*, Chaoran and Guan*, Jiaqi and Ren, Milong and Gong, Chengyue and Liu, Cong and Chen, Xinshi and Liu, Ge and Xiao, Wenzhi},journal = {arXiv preprint arXiv:2605.03360},year = {2026},}
Accurate de novo Design of Peptides from Programming Biophysical Landscape
Mingyu Li, Yini Liu, Jie Zhong, Xinchao Shi, Jiqing Zheng, Kai Wang, Yunxia Cui, Chaoran Cheng, Shijin Li, Xiangzhe Kong, Shaoning Li, Miaojie Xv, Chunhao Zhu, Xiaobing Lan, He Yang, Kewei Chang, Zhenyu An, Shizhang Wan, Xiuyan Yang, Qiancheng Shen, H. Eric Xu, Zihua Wang, Lei Liu, Youwen Zhuang, Jianzhu Ma, and Jian Zhang
@article{li2026accurate,title={Accurate de novo Design of Peptides from Programming Biophysical Landscape},author={Li, Mingyu and Liu, Yini and Zhong, Jie and Shi, Xinchao and Zheng, Jiqing and Wang, Kai and Cui, Yunxia and Cheng, Chaoran and Li, Shijin and Kong, Xiangzhe and Li, Shaoning and Xv, Miaojie and Zhu, Chunhao and Lan, Xiaobing and Yang, He and Chang, Kewei and An, Zhenyu and Wan, Shizhang and Yang, Xiuyan and Shen, Qiancheng and Xu, H. Eric and Wang, Zihua and Liu, Lei and Zhuang, Youwen and Ma, Jianzhu and Zhang, Jian},journal={bioRxiv},year={2026},doi={10.64898/2026.06.08.731011},}
h-MINT: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network
Yanru Qu, Yijie Zhang, Wenjuan Tan, Xiangzhe Kong, Xiangxin Zhou, Chaoran Cheng, Mathieu Blanchette, Jiaxuan You, and Ge Liu
In The Fourteenth International Conference on Learning Representations 2026
@inproceedings{qu2026hmint,title={{h-MINT}: Modeling Pocket-Ligand Binding with Hierarchical Molecular Interaction Network},author={Qu, Yanru and Zhang, Yijie and Tan, Wenjuan and Kong, Xiangzhe and Zhou, Xiangxin and Cheng, Chaoran and Blanchette, Mathieu and You, Jiaxuan and Liu, Ge},booktitle={The Fourteenth International Conference on Learning Representations},year={2026},}
LangFlow: Continuous Diffusion Rivals Discrete in Language Modeling
Yuxin Chen, Chumeng Liang, Hangke Sui, Ruihan Guo, Chaoran Cheng, Jiaxuan You, and Ge Liu
@article{chen2026langflow,title={{LangFlow}: Continuous Diffusion Rivals Discrete in Language Modeling},author={Chen, Yuxin and Liang, Chumeng and Sui, Hangke and Guo, Ruihan and Cheng, Chaoran and You, Jiaxuan and Liu, Ge},journal={arXiv preprint arXiv:2604.11748},year={2026},}
M3: High-Fidelity Text-to-Image Generation via Multi-Modal, Multi-Agent and Multi-Round Visual Reasoning
Bangji Yang, Ruihan Guo, Jiajun Fan, Chaoran Cheng, and Ge Liu
@article{yang2026m3,title={{M3}: High-Fidelity Text-to-Image Generation via Multi-Modal, Multi-Agent and Multi-Round Visual Reasoning},author={Yang, Bangji and Guo, Ruihan and Fan, Jiajun and Cheng, Chaoran and Liu, Ge},journal={arXiv preprint arXiv:2602.06166},year={2026},}
MutAtlas: A PDB-Wide Energy-Guided Atlas of Protein Mutation Effects
Ruihan Guo*, Chaoran Cheng*, Zhanghan Ni, Neil He, Bangji Yang, and Ge Liu
In Proceedings of the 43rd International Conference on Machine Learning 2026
@inproceedings{guo2026mutatlas,title={{MutAtlas}: A {PDB}-Wide Energy-Guided Atlas of Protein Mutation Effects},author={Guo*, Ruihan and Cheng*, Chaoran and Ni, Zhanghan and He, Neil and Yang, Bangji and Liu, Ge},booktitle={Proceedings of the 43rd International Conference on Machine Learning},series={Proceedings of Machine Learning Research},volume={306},publisher={PMLR},year={2026},}
Fine-Tuning Flow Matching Generative Models with Intermediate Feedback
Jiajun Fan, Chaoran Cheng, Shuaike Shen, Xiangxin Zhou, and Ge Liu
@inproceedings{fan2026intermediate,title={Fine-Tuning Flow Matching Generative Models with Intermediate Feedback},author={Fan, Jiajun and Cheng, Chaoran and Shen, Shuaike and Zhou, Xiangxin and Liu, Ge},booktitle={2nd DeLTa Workshop at ICLR 2026},year={2026},}
Learning Protein Structure Representation with Orientation-Aware Networks
Jiahan Li, Shitong Luo, Congyue Deng, Chaoran Cheng, Jiaqi Guan, Leonidas Guibas, Jian Peng, and Jianzhu Ma
@article{li2026orientation,title={Learning Protein Structure Representation with Orientation-Aware Networks},author={Li, Jiahan and Luo, Shitong and Deng, Congyue and Cheng, Chaoran and Guan, Jiaqi and Guibas, Leonidas and Peng, Jian and Ma, Jianzhu},journal={Journal of Computational Biology},volume={33},number={1},pages={90--106},year={2026},doi={10.1177/15578666251406300},}
2025
Riemannian Consistency Model
Chaoran Cheng*, Yusong Wang*, Yuxin Chen, Xiangxin Zhou, Nanning Zheng, and Ge Liu
In Advances in Neural Information Processing Systems 2025
@inproceedings{cheng2025riemannian,title={Riemannian Consistency Model},author={Cheng*, Chaoran and Wang*, Yusong and Chen, Yuxin and Zhou, Xiangxin and Zheng, Nanning and Liu, Ge},booktitle={Advances in Neural Information Processing Systems},volume={38},pages={80745--80775},year={2025},}
Adaptive Divergence Regularized Policy Optimization for Fine-Tuning Generative Models
Jiajun Fan, Tong Wei, Chaoran Cheng, Yuxin Chen, and Ge Liu
In Advances in Neural Information Processing Systems 2025
@inproceedings{fan2025adaptive,title={Adaptive Divergence Regularized Policy Optimization for Fine-Tuning Generative Models},author={Fan, Jiajun and Wei, Tong and Cheng, Chaoran and Chen, Yuxin and Liu, Ge},booktitle={Advances in Neural Information Processing Systems},volume={38},pages={124070--124107},year={2025},}
MSAFlow: A Unified Approach for MSA Representation, Augmentation, and Family-Based Protein Design
Aishwarya Venkatraman, He Cao, Tong Wei, Chaoran Cheng, and Ge Liu
@inproceedings{venkatraman2025msaflow,title={{MSAFlow}: A Unified Approach for {MSA} Representation, Augmentation, and Family-Based Protein Design},author={Venkatraman, Aishwarya and Cao, He and Wei, Tong and Cheng, Chaoran and Liu, Ge},booktitle={NeurIPS 2025 Workshop on AI for Science},year={2025},}
α-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models
@article{cheng2025alphaflow,title={{α-Flow}: A Unified Framework for Continuous-State Discrete Flow Matching Models},author={Cheng, Chaoran and Li, Jiahan and Fan, Jiajun and Liu, Ge},journal={arXiv preprint arXiv:2504.10283},year={2025},}
Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization
Jiajun Fan, Shuaike Shen, Chaoran Cheng, Yuxin Chen, Chumeng Liang, and Ge Liu
In The Thirteenth International Conference on Learning Representations 2025
@inproceedings{fan2025online,title={Online Reward-Weighted Fine-Tuning of Flow Matching with Wasserstein Regularization},author={Fan, Jiajun and Shen, Shuaike and Cheng, Chaoran and Chen, Yuxin and Liang, Chumeng and Liu, Ge},booktitle={The Thirteenth International Conference on Learning Representations},year={2025},}
Gradient-Free Generation for Hard-Constrained Systems
Chaoran Cheng, Boran Han, Danielle C. Maddix, Abdul Fatir Ansari, Andrew Stuart, Michael W. Mahoney, and Bernie Wang
In The Thirteenth International Conference on Learning Representations 2025
@inproceedings{cheng2025gradientfree,title={Gradient-Free Generation for Hard-Constrained Systems},author={Cheng, Chaoran and Han, Boran and Maddix, Danielle C. and Ansari, Abdul Fatir and Stuart, Andrew and Mahoney, Michael W. and Wang, Bernie},booktitle={The Thirteenth International Conference on Learning Representations},year={2025},}
Training-Free Guided Flow Matching with Optimal Control
Luran Wang, Chaoran Cheng, Yizhen Liao, Yanru Qu, and Ge Liu
In The Thirteenth International Conference on Learning Representations 2025
@inproceedings{wang2025training,title={Training-Free Guided Flow Matching with Optimal Control},author={Wang, Luran and Cheng, Chaoran and Liao, Yizhen and Qu, Yanru and Liu, Ge},booktitle={The Thirteenth International Conference on Learning Representations},year={2025},}
Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension
Jiahan Li, Tong Chen, Shitong Luo, Chaoran Cheng, Jiaqi Guan, Ruihan Guo, Sheng Wang, Ge Liu, Jian Peng, and Jianzhu Ma
In The Thirteenth International Conference on Learning Representations 2025
@inproceedings{li2025hotspot,title={Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension},author={Li, Jiahan and Chen, Tong and Luo, Shitong and Cheng, Chaoran and Guan, Jiaqi and Guo, Ruihan and Wang, Sheng and Liu, Ge and Peng, Jian and Ma, Jianzhu},booktitle={The Thirteenth International Conference on Learning Representations},year={2025},}
2024
Geometric Point Attention Transformer for 3D Shape Reassembly
@article{li2024gpat,title={Geometric Point Attention Transformer for 3D Shape Reassembly},author={Li, Jiahan and Cheng, Chaoran and Ma, Jianzhu and Liu, Ge},journal={arXiv preprint arXiv:2411.17788},year={2024},}
Ab Initio Characterization of Protein Molecular Dynamics with AI2BMD
Tong Wang, Xinheng He, Mingyu Li, Yatao Li, Ran Bi, Yusong Wang, Chaoran Cheng, Xiangzhen Shen, Jiawei Meng, He Zhang, Haiguang Liu, Zun Wang, Shaoning Li, Bin Shao, and Tie-Yan Liu
@article{wang2024ai2bmd,title={Ab Initio Characterization of Protein Molecular Dynamics with {AI2BMD}},author={Wang, Tong and He, Xinheng and Li, Mingyu and Li, Yatao and Bi, Ran and Wang, Yusong and Cheng, Chaoran and Shen, Xiangzhen and Meng, Jiawei and Zhang, He and Liu, Haiguang and Wang, Zun and Li, Shaoning and Shao, Bin and Liu, Tie-Yan},journal={Nature},volume={635},number={8040},pages={1019--1027},year={2024},doi={10.1038/s41586-024-08127-z},}
Neural P³M: A Long-Range Interaction Modeling Enhancer for Geometric GNNs
Yusong Wang*, Chaoran Cheng*, Shaoning Li*, Yuxuan Ren, Bin Shao, Ge Liu, Pheng-Ann Heng, and Nanning Zheng
In Advances in Neural Information Processing Systems 2024
@inproceedings{wang2024neuralp3m,title={Neural P³M: A Long-Range Interaction Modeling Enhancer for Geometric {GNNs}},author={Wang*, Yusong and Cheng*, Chaoran and Li*, Shaoning and Ren, Yuxuan and Shao, Bin and Liu, Ge and Heng, Pheng-Ann and Zheng, Nanning},booktitle={Advances in Neural Information Processing Systems},volume={37},pages={120336--120365},year={2024},}
Full-Atom Peptide Design Based on Multi-Modal Flow Matching
Jiahan Li, Chaoran Cheng, Zuofan Wu, Ruihan Guo, Shitong Luo, Zhizhou Ren, Jian Peng, and Jianzhu Ma
In Proceedings of the 41st International Conference on Machine Learning 2024
@inproceedings{li2024pepflow,title={Full-Atom Peptide Design Based on Multi-Modal Flow Matching},author={Li, Jiahan and Cheng, Chaoran and Wu, Zuofan and Guo, Ruihan and Luo, Shitong and Ren, Zhizhou and Peng, Jian and Ma, Jianzhu},booktitle={Proceedings of the 41st International Conference on Machine Learning},series={Proceedings of Machine Learning Research},volume={235},pages={27615--27640},publisher={PMLR},year={2024},}
Categorical Flow Matching on Statistical Manifolds
Chaoran Cheng, Jiahan Li, Jian Peng, and Ge Liu
In Advances in Neural Information Processing Systems 2024
@inproceedings{cheng2024categorical,title={Categorical Flow Matching on Statistical Manifolds},author={Cheng, Chaoran and Li, Jiahan and Peng, Jian and Liu, Ge},booktitle={Advances in Neural Information Processing Systems},volume={37},pages={54787--54819},year={2024},}
2023
Equivariant Neural Operator Learning with Graphon Convolution
Chaoran Cheng, and Jian Peng
In Advances in Neural Information Processing Systems 2023
@inproceedings{cheng2023infgcn,title={Equivariant Neural Operator Learning with Graphon Convolution},author={Cheng, Chaoran and Peng, Jian},booktitle={Advances in Neural Information Processing Systems},volume={36},pages={61960--61984},year={2023},}
2022
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing
Shitong Luo, Jiahan Li, Jiaqi Guan, Yufeng Su, Chaoran Cheng, Jian Peng, and Jianzhu Ma
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2022
@inproceedings{luo2022equivariant,title={Equivariant Point Cloud Analysis via Learning Orientations for Message Passing},author={Luo, Shitong and Li, Jiahan and Guan, Jiaqi and Su, Yufeng and Cheng, Chaoran and Peng, Jian and Ma, Jianzhu},booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},pages={18932--18941},year={2022},}
DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation
Yifan Wang, Yiping Song, Shuai Li, Chaoran Cheng, Wei Ju, Ming Zhang, and Sheng Wang
Proceedings of the AAAI Conference on Artificial Intelligence 2022
@article{wang2022disencite,title={{DisenCite}: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation},author={Wang, Yifan and Song, Yiping and Li, Shuai and Cheng, Chaoran and Ju, Wei and Zhang, Ming and Wang, Sheng},journal={Proceedings of the AAAI Conference on Artificial Intelligence},volume={36},number={10},pages={11449--11458},year={2022},doi={10.1609/aaai.v36i10.21397},}