Fang Wu - RankMe

51 papers A* 10Journal 37Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modeling. CoRR Fang Wu, Stan Z. Li
2026	J	`jnl`	LatentChem: From Textual CoT to Latent Thinking in Chemical Reasoning. CoRR Xinwu Ye, Yicheng Mao, Jia Zhang, Yimeng Liu, Li Hao, Fang Wu, Zhiwei Li, Yuxuan Liao, Zehong Wang, Zhiyuan Liu, Zhenfei Yin, Li Yuan, Philip Torr, Huan Sun, Xiangxiang Zeng, Mengdi Wang, Le Cong, Shenghua Gao, Xiangru Tang
2026	J	`jnl`	Molecular Representations in Implicit Functional Space via Hyper-Networks. CoRR Zehong Wang, Xiaolong Han, Qi Yang, Xiangru Tang, Fang Wu, Xiaoguang Guo, Weixiang Sun, Tianyi Ma, Pietro Lio, Le Cong, Sheng Wang, Chuxu Zhang, Yanfang Ye
2026	J	`jnl`	RiboSphere: Learning Unified and Efficient Representations of RNA Structures. CoRR Zhou Zhang, Hanqun Cao, Cheng Tan, Fang Wu, Pheng-Ann Heng, Tianfan Fu
2026	J	`jnl`	Surface-based Molecular Design with Multi-modal Flow Matching. CoRR Fang Wu, Zhengyuan Zhou, Shuting Jin, Xiangxiang Zeng, Jure Leskovec, Jinbo Xu
2026	J	`jnl`	Toward Global Large Language Models in Medicine. CoRR Rui Yang, Huitao Li, Weihao Xuan, Heli Qi, Xin Li, Kunyu Yu, Yingjian Chen, Rongrong Wang, Jacques Behmoaras, Tianxi Cai, Bibhas Chakraborty, Qingyu Chen, Lionel Tim-Ee Cheng, Marie-Louise Damwanza, Chido Dzinotyiwei, Aosong Feng, Chuan Hong, Yusuke Iwasawa, Yuhe Ke, Linah Kitala, Taehoon Ko, Jisan Lee, Irene Li, Jonathan Chong Kai Liew, Hongfang Liu, Lian Leng Low, Edison Marrese-Taylor, Yutaka Matsuo, Isheanesu Misi, Yilin Ning, Jasmine Chiat Ling Ong, Marcus Eng Hock Ong, Enrico Petretto, Hossein Rouhizadeh, Abiram Sandralegar, Oren Schreier, Iain Bee Huat Tan, Patrick Tan, Daniel Shu Wei Ting, Junjue Wang, Chunhua Weng, Matthew Yu Heng Wong, Fang Wu, Yunze Xiao, Xuhai Xu, Qingcheng Zeng, Zhuo Zheng, Yifan Peng, Douglas Teodoro, Nan Liu
2026	J	`jnl`	W2T: LoRA Weights Already Know What They Can Do. CoRR Xiaolong Han, Ferrante Neri, Zijian Jiang, Fang Wu, Yanfang Ye, Lu Yin, Zehong Wang
2026	J	`jnl`	Why Reasoning Fails to Plan: A Planning-Centric Analysis of Long-Horizon Decision Making in LLM Agents. CoRR Zehong Wang, Fang Wu, Hongru Wang, Xiangru Tang, Bolian Li, Zhenfei Yin, Yijun Ma, Yiyang Li, Weixiang Sun, Xiusi Chen, Yanfang Ye
2025	J	`jnl`	A deep reinforcement learning platform for antibiotic discovery. CoRR 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
2025	J	`jnl`	BroRL: Scaling Reinforcement Learning via Broadened Exploration. CoRR Jian Hu, Mingjie Liu, Ximing Lu, Fang Wu, Zaïd Harchaoui, Shizhe Diao, Yejin Choi, Pavlo Molchanov, June Yang, Jan Kautz, Yi Dong
2025	J	`jnl`	DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search. CoRR Fang Wu, Weihao Xuan, Heli Qi, Ximing Lu, Aaron Tu, Li Erran Li, Yejin Choi
2025	J	`jnl`	Diagnose, Localize, Align: A Full-Stack Framework for Reliable LLM Multi-Agent Systems under Instruction Conflicts. CoRR 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
2025	J	`jnl`	Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modeling. Trans. Mach. Learn. Res. Fang Wu, Stan Z. Li
2025	J	`jnl`	From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning? CoRR 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
2025	A*	`conf`	Generalized Implicit Neural Representations for Dynamic Molecular Surface Modeling. AAAI Fang Wu, Bozhen Hu, Stan Z. Li
2025	J	`jnl`	L^2M^3OF: A Large Language Multimodal Model for Metal-Organic Frameworks. CoRR Jiyu Cui, Fang Wu, Haokai Zhao, Minggao Feng, Xenophon Evangelopoulos, Andrew I. Cooper, Yejin Choi
2025	—	`conf`	Large Language Models are Good Relational Learners. ACL (1) Fang Wu, Vijay Prakash Dwivedi, Jure Leskovec
2025	J	`jnl`	Large Language Models are Good Relational Learners. CoRR Fang Wu, Vijay Prakash Dwivedi, Jure Leskovec
2025	J	`jnl`	Life-Code: Central Dogma Modeling with Multi-Omics Sequence Unification. CoRR Zicheng Liu, Siyuan Li, Zhiyuan Chen, Lei Xin, Fang Wu, Chang Yu, Qirong Yang, Yucheng Guo, Yujie Yang, Stan Z. Li
2025	J	`jnl`	Multiplayer Nash Preference Optimization. CoRR Fang Wu, Xu Huang, Weihao Xuan, Zhiwei Zhang, Yijia Xiao, Guancheng Wan, Xiaomin Li, Bing Hu, Peng Xia, Jure Leskovec, Yejin Choi
2025	J	`jnl`	PoseX: AI Defeats Physics Approaches on Protein-Ligand Cross Docking. CoRR 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
2025	J	`jnl`	Position: The Hidden Costs and Measurement Gaps of Reinforcement Learning with Verifiable Rewards. CoRR 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
2025	A*	`conf`	Predicting mutational effects on protein binding from folding energy. ICML Arthur Deng, Karsten D. Householder, Fang Wu, K. Christopher Garcia, Brian L. Trippe
2025	J	`jnl`	Predicting mutational effects on protein binding from folding energy. CoRR Arthur Deng, Karsten D. Householder, Fang Wu, Sebastian Thrun, K. Christopher Garcia, Brian L. Trippe
2025	—	`conf`	Retrieval-Reasoning Large Language Model-based Synthetic Clinical Trial Generation. BCB Zerui Xu, Fang Wu, Yingzhou Lu, Yuanyuan Zhang, Yue Zhao
2025	—	`conf`	Surface-based Molecular Design with Multi-modal Flow Matching. KDD (2) Fang Wu, Zhengyuan Zhou, Shuting Jin, Xiangxiang Zeng, Jure Leskovec, Jinbo Xu
2025	J	`jnl`	The Invisible Leash: Why RLVR May Not Escape Its Origin. CoRR Fang Wu, Weihao Xuan, Ximing Lu, Zaïd Harchaoui, Yejin Choi
2025	J	`jnl`	When to Trust Context: Self-Reflective Debates for Context Reliability. CoRR Zeqi Zhou, Fang Wu, Shayan Talaei, Haokai Zhao, Cheng Meixin, Tinson Xu, Amin Saberi, Yejin Choi
2024	J	`jnl`	Discovering the Representation Bottleneck of Graph Neural Networks. IEEE Trans. Knowl. Data Eng. Fang Wu, Siyuan Li, Stan Z. Li
2024	—	`conf`	InsertGNN: A Hierarchical Graph Neural Network for the TOEFL Sentence Insertion Problem. EMNLP (Findings) Fang Wu, Stan Z. Li
2024	A*	`conf`	Instructor-inspired Machine Learning for Robust Molecular Property Prediction. NeurIPS Fang Wu, Shuting Jin, Siyuan Li, Stan Z. Li
2024	J	`jnl`	Retrieval-Reasoning Large Language Model-based Synthetic Clinical Trial Generation. CoRR Zerui Xu, Fang Wu, Tianfan Fu, Yue Zhao
2024	A*	`conf`	SemiReward: A General Reward Model for Semi-supervised Learning. ICLR Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li
2024	A*	`conf`	Surface-VQMAE: Vector-quantized Masked Auto-encoders on Molecular Surfaces. ICML Fang Wu, Stan Z. Li
2023	A*	`conf`	A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design. NeurIPS Fang Wu, Stan Z. Li
2023	J	`jnl`	A Hierarchical Training Paradigm for Antibody Structure-sequence Co-design. CoRR Fang Wu, Stan Z. Li
2023	A*	`conf`	Architecture-Agnostic Masked Image Modeling - From ViT back to CNN. ICML Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Stan Z. Li
2023	A*	`conf`	DiffMD: A Geometric Diffusion Model for Molecular Dynamics Simulations. AAAI Fang Wu, Stan Z. Li
2023	J	`jnl`	Explaining Graph Neural Networks via Non-parametric Subgraph Matching. CoRR Fang Wu, Siyuan Li, Lirong Wu, Dragomir Radev, Yinghui Jiang, Xurui Jin, Zhangming Niu, Stan Z. Li
2023	J	`jnl`	Improving molecular representation learning with metric learning-enhanced optimal transport. Patterns Fang Wu, Nicolas Courty, Shuting Jin, Stan Z. Li
2023	J	`jnl`	InstructBio: A Large-scale Semi-supervised Learning Paradigm for Biochemical Problems. CoRR Fang Wu, Huiling Qin, Siyuan Li, Stan Z. Li, Xianyuan Zhan, Jinbo Xu
2023	A*	`conf`	Molformer: Motif-Based Transformer on 3D Heterogeneous Molecular Graphs. AAAI Fang Wu, Dragomir Radev, Stan Z. Li
2023	A*	`conf`	Rethinking Explaining Graph Neural Networks via Non-parametric Subgraph Matching. ICML Fang Wu, Siyuan Li, Xurui Jin, Yinghui Jiang, Dragomir Radev, Zhangming Niu, Stan Z. Li
2023	J	`jnl`	SemiReward: A General Reward Model for Semi-supervised Learning. CoRR Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li
2022	J	`jnl`	A Score-based Geometric Model for Molecular Dynamics Simulations. CoRR Fang Wu, Qiang Zhang, Xurui Jin, Yinghui Jiang, Stan Z. Li
2022	J	`jnl`	Architecture-Agnostic Masked Image Modeling - From ViT back to CNN. CoRR Siyuan Li, Di Wu, Fang Wu, Zelin Zang, Kai Wang, Lei Shang, Baigui Sun, Hao Li, Stan Z. Li
2022	J	`jnl`	Discovering the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions. CoRR Fang Wu, Siyuan Li, Lirong Wu, Dragomir R. Radev, Qiang Zhang, Stan Z. Li
2022	J	`jnl`	Metric Learning-enhanced Optimal Transport for Biochemical Regression Domain Adaptation. CoRR Fang Wu, Nicolas Courty, Zhang Qiang, Jiyu Cui, Ziqing Li
2022	J	`jnl`	Pre-training of Deep Protein Models with Molecular Dynamics Simulations for Drug Binding. CoRR Fang Wu, Qiang Zhang, Dragomir R. Radev, Yuyang Wang, Xurui Jin, Yinghui Jiang, Zhangming Niu, Stan Z. Li
2022	J	`jnl`	When Geometric Deep Learning Meets Pretrained Protein Language Models. CoRR Fang Wu, Tao Yu, Dragomir Radev, Jinbo Xu
2021	J	`jnl`	3D-Transformer: Molecular Representation with Transformer in 3D Space. CoRR Fang Wu, Qiang Zhang, Dragomir R. Radev, Jiyu Cui, Wen Zhang, Huabin Xing, Ningyu Zhang, Huajun Chen