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ORCIDFang Wu 0002
Person information
- affiliation: Stanford University, CA, USA
- affiliation (2019 - 2021): Columbia University, NY, USA
Other persons with the same name
- Fang Wu — disambiguation page
- Fang Wu 0001 — Hewlett Packard Laboratories, USA
- Fang Wu 0003
![[0000-0003-2365-6283]](https://dblp.uni-trier.de/img/orcid-mark.12x12.png "0000-0003-2365-6283")
— Desay SV Automotive, Singapore (and 1 more) - Fang Wu 0004 — Harbin Institute of Technology, Heilongjiang, China
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2020 – today
- 2025
[j3]Fang Wu, Stan Z. Li:
Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modeling. Trans. Mach. Learn. Res. 2025 (2025)- [c13]Fang Wu, Bozhen Hu, Stan Z. Li:
Generalized Implicit Neural Representations for Dynamic Molecular Surface Modeling. AAAI 2025: 877-885 - [c12]Fang Wu, Vijay Prakash Dwivedi, Jure Leskovec:
Large Language Models are Good Relational Learners. ACL (1) 2025: 7835-7854 - [c11]Arthur Deng, Karsten D. Householder, Fang Wu, K. Christopher Garcia, Brian L. Trippe:
Predicting mutational effects on protein binding from folding energy. ICML 2025 - [c10]Fang Wu, Zhengyuan Zhou, Shuting Jin, Xiangxiang Zeng, Jure Leskovec, Jinbo Xu:
Surface-based Molecular Design with Multi-modal Flow Matching. KDD (2) 2025: 3192-3203 - [i22]Zicheng Liu, Siyuan Li, Zhiyuan Chen, Lei Xin, Fang Wu, Chang Yu, Qirong Yang, Yucheng Guo, Yujie Yang, Stan Z. Li:
Life-Code: Central Dogma Modeling with Multi-Omics Sequence Unification. CoRR abs/2502.07299 (2025) - [i21]Yize Jiang, Xinze Li, Yuanyuan Zhang, Jin Han, Youjun Xu, Ayush Pandit, Zaixi Zhang, Mengdi Wang, Mengyang Wang, Chong Liu, Guang Yang, Yejin Choi, Wu-Jun Li, Tianfan Fu, Fang Wu, Junhong Liu:
PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking. CoRR abs/2505.01700 (2025) - [i20]Fang Wu, Vijay Prakash Dwivedi, Jure Leskovec:
Large Language Models are Good Relational Learners. CoRR abs/2506.05725 (2025) - [i19]Arthur Deng, Karsten D. Householder, Fang Wu, Sebastian Thrun, K. Christopher Garcia, Brian L. Trippe:
Predicting mutational effects on protein binding from folding energy. CoRR abs/2507.05502 (2025) - [i18]Fang Wu, Weihao Xuan, Ximing Lu, Zaïd Harchaoui, Yejin Choi:
The Invisible Leash: Why RLVR May Not Escape Its Origin. CoRR abs/2507.14843 (2025) - [i17]Hanqun Cao, Marcelo Der Torossian Torres, Jingjie Zhang, Zijun Gao, Fang Wu, Chunbin Gu, Jure Leskovec, Yejin Choi, Cesar de la Fuente-Nunez, Guangyong Chen, Pheng-Ann Heng:
A deep reinforcement learning platform for antibiotic discovery. CoRR abs/2509.18153 (2025) - [i16]Aaron Tu, Weihao Xuan, Heli Qi, Xu Huang, Qingcheng Zeng, Shayan Talaei, Yijia Xiao, Peng Xia, Xiangru Tang, Yuchen Zhuang, Bing Hu, Hanqun Cao, Wenqi Shi, Tianang Leng, Rui Yang, Yingjian Chen, Ziqi Wang, Irene Li, Nan Liu, Huaxiu Yao, Li Erran Li, Ge Liu, Amin Saberi, Naoto Yokoya, Jure Leskovec, Yejin Choi, Fang Wu:
Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards. CoRR abs/2509.21882 (2025) - [i15]Fang Wu, Xu Huang, Weihao Xuan, Zhiwei Zhang, Yijia Xiao, Guancheng Wan, Xiaomin Li, Bing Hu, Peng Xia, Jure Leskovec, Yejin Choi:
Multiplayer Nash Preference Optimization. CoRR abs/2509.23102 (2025) - [i14]Guancheng Wan, Leixin Sun, Longxu Dou, Zitong Shi, Fang Wu, Eric Hanchen Jiang, Wenke Huang, Guibin Zhang, Hejia Geng, Xiangru Tang, Zhenfei Yin, Yizhou Sun, Wei Wang:
Diagnose, Localize, Align: A Full-Stack Framework for Reliable LLM Multi-Agent Systems under Instruction Conflicts. CoRR abs/2509.23188 (2025) - [i13]Fang Wu, Weihao Xuan, Heli Qi, Ximing Lu, Aaron Tu, Li Erran Li, Yejin Choi:
DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search. CoRR abs/2509.25454 (2025) - [i12]Hanqun Cao, Hongrui Zhang, Junde Xu, Zhou Zhang, Lingdong Shen, Minghao Sun, Ge Liu, Jinbo Xu, Wu-Jun Li, Jinren Ni, Cesar de la Fuente-Nunez, Tianfan Fu, Yejin Choi, Pheng-Ann Heng, Fang Wu:
From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning? CoRR abs/2510.01571 (2025) - 2024
- [j2]Fang Wu, Siyuan Li, Stan Z. Li:
Discovering the Representation Bottleneck of Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(12): 7998-8008 (2024) - [c9]Fang Wu, Stan Z. Li:
InsertGNN: A Hierarchical Graph Neural Network for the TOEFL Sentence Insertion Problem. EMNLP (Findings) 2024: 173-180 - [c8]Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li:
SemiReward: A General Reward Model for Semi-supervised Learning. ICLR 2024 - [c7]Fang Wu, Stan Z. Li:
Surface-VQMAE: Vector-quantized Masked Auto-encoders on Molecular Surfaces. ICML 2024 - [c6]Fang Wu, Shuting Jin, Siyuan Li, Stan Z. Li:
Instructor-inspired Machine Learning for Robust Molecular Property Prediction. NeurIPS 2024 - 2023
- [j1]Fang Wu, Nicolas Courty, Shuting Jin, Stan Z. Li:
Improving molecular representation learning with metric learning-enhanced optimal transport. Patterns 4(4): 100714 (2023) - [c5]Fang Wu, Dragomir Radev, Stan Z. Li:
Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs. AAAI 2023: 5312-5320 - [c4]Fang Wu, Stan Z. Li:
DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations. AAAI 2023: 5321-5329 - [c3]Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Stan Z. Li:
Architecture-Agnostic Masked Image Modeling - From ViT back to CNN. ICML 2023: 20149-20167 - [c2]Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev, Zhangming Niu, Stan Z. Li:
Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching. ICML 2023: 37511-37523 - [c1]Fang Wu, Stan Z. Li:
A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design. NeurIPS 2023 - [i11]Fang Wu, Siyuan Li, Lirong Wu, Dragomir Radev, Yinghui Jiang, Xurui Jin, Zhangming Niu, Stan Z. Li:
Explaining Graph Neural Networks via Non-parametric Subgraph Matching. CoRR abs/2301.02780 (2023) - [i10]Fang Wu, Huiling Qin, Siyuan Li, Stan Z. Li, Xianyuan Zhan, Jinbo Xu:
InstructBio: A Large-scale Semi-supervised Learning Paradigm for Biochemical Problems. CoRR abs/2304.03906 (2023) - [i9]Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li:
SemiReward: A General Reward Model for Semi-supervised Learning. CoRR abs/2310.03013 (2023) - [i8]Fang Wu, Stan Z. Li:
A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design. CoRR abs/2311.16126 (2023) - 2022
- [i7]Fang Wu, Nicolas Courty, Zhang Qiang, Jiyu Cui, Ziqing Li:
Metric Learning-enhanced Optimal Transport for Biochemical Regression Domain Adaptation. CoRR abs/2202.06208 (2022) - [i6]Fang Wu, Qiang Zhang, Dragomir R. Radev, Yuyang Wang, Xurui Jin, Yinghui Jiang, Zhangming Niu, Stan Z. Li:
Pre-training of Deep Protein Models with Molecular Dynamics Simulations for Drug Binding. CoRR abs/2204.08663 (2022) - [i5]Fang Wu, Qiang Zhang, Xurui Jin, Yinghui Jiang, Stan Z. Li:
A Score-based Geometric Model for Molecular Dynamics Simulations. CoRR abs/2204.08672 (2022) - [i4]Fang Wu, Siyuan Li, Lirong Wu, Dragomir R. Radev, Qiang Zhang, Stan Z. Li:
Discovering the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions. CoRR abs/2205.07266 (2022) - [i3]Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li:
Architecture-Agnostic Masked Image Modeling - From ViT back to CNN. CoRR abs/2205.13943 (2022) - [i2]Fang Wu, Tao Yu, Dragomir Radev, Jinbo Xu:
When Geometric Deep Learning Meets Pretrained Protein Language Models. CoRR abs/2212.03447 (2022) - 2021
- [i1]Fang Wu, Qiang Zhang, Dragomir R. Radev, Jiyu Cui, Wen Zhang, Huabin Xing, Ningyu Zhang, Huajun Chen:
3D-Transformer: Molecular Representation with Transformer in 3D Space. CoRR abs/2110.01191 (2021)
Coauthor Index
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