Yufei Huang

According to our database, Yufei Huang authored at least 53 papers between 2022 and 2026.

Collaborative distances:

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

2026

Improving Diffusion Generalization with Weak-to-Strong Segmented Guidance.

Liangyu Yuan, Yufei Huang, Mingkun Lei, Tong Zhao, Ruoyu Wang, Changxi Chi, Yiwei Wang, Chi Zhang

CoRR, March, 2026

VitaMol: Lightweight molecular modality expansion in discrete space for multi-task transfer learning.

Yunfan Liu, Zhifeng Gao, Lirong Wu, Jingbo Zhou, Tongyue Xu, Cheng Tan, Yufei Huang, Changxi Chi, Chang Yu, Stan Z. Li

Pattern Recognit., 2026

VecFormer: Towards Efficient and Generalizable Graph Transformer with Graph Token Attention.

Jingbo Zhou, Jun Xia, Siyuan Li, Yunfan Liu, Wenjun Wang, Yufei Huang, Changxi Chi, Mutian Hong, Zhuoli Ouyang, Shu Wang, Zhongqi Wang, Xingyu Wu, Chang Yu, Stan Z. Li

Proceedings of the ACM Web Conference 2026, 2026

Departures: Distributional Transport for Single-Cell Perturbation Prediction with Neural Schrödinger Bridges.

Changxi Chi, Yufei Huang, Jun Xia, Jiangbin Zheng, Yunfan Liu, Zelin Zang, Stan Z. Li

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

ECloudGen: leveraging electron clouds as a latent variable to scale up structure-based molecular design.

Odin Zhang, Jieyu Jin, Zhenxing Wu, Jintu Zhang, Po Yuan, Yuntao Yu, Haitao Lin, Haiyang Zhong, Xujun Zhang, Chenqing Hua, Weibo Zhao, Zhengshuo Zhang, Kejun Ying, Yufei Huang, Huifeng Zhao, Yu Kang, Peichen Pan, Jike Wang, Dong Guo, Shuangjia Zheng, Chang-Yu Hsieh, Tingjun Hou

Nat. Comput. Sci., November, 2025

Unlasting: Unpaired Single-Cell Multi-Perturbation Estimation by Dual Conditional Diffusion Implicit Bridges.

Changxi Chi, Jun Xia, Yufei Huang, Jingbo Zhou, Siyuan Li, Yunfan Liu, Chang Yu, Stan Z. Li

CoRR, June, 2025

AlphaFold Database Debiasing for Robust Inverse Folding.

Cheng Tan, Zhenxiao Cao, Zhangyang Gao, Siyuan Li, Yufei Huang, Stan Z. Li

CoRR, June, 2025

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning.

Haitao Lin, Odin Zhang, Jia Xu, Yunfan Liu, Zheng Chen, Lirong Wu, Yufei Huang, Zhifeng Gao, Stan Z. Li

CoRR, May, 2025

VARD: Efficient and Dense Fine-Tuning for Diffusion Models with Value-based RL.

Fengyuan Dai, Zifeng Zhuang, Yufei Huang, Siteng Huang, Bangyan Liao, Donglin Wang, Fajie Yuan

CoRR, May, 2025

A Simple yet Effective DDG Predictor is An Unsupervised Antibody Optimizer and Explainer.

Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Guojiang Zhao, Zhifeng Gao, Stan Z. Li

CoRR, February, 2025

Durian: A Comprehensive Benchmark for Structure-Based 3D Molecular Generation.

Dou Nie, Huifeng Zhao, Odin Zhang, Gaoqi Weng, Hui Zhang, Jieyu Jin, Haitao Lin, Yufei Huang, Liwei Liu, Dan Li, Tingjun Hou, Yu Kang

J. Chem. Inf. Model., 2025

A Simple yet Effective ΔΔG Predictor is An Unsupervised Antibody Optimizer and Explainer.

Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Guojiang Zhao, Zhifeng Gao, Stan Z. Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph.

Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Cheng Tan, Zicheng Liu, Zhifeng Gao, Stan Z. Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction.

Cheng Tan, Zhenxiao Cao, Zhangyang Gao, Lirong Wu, Siyuan Li, Yufei Huang, Jun Xia, Bozhen Hu, Stan Z. Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

EVA: Geometric Inverse Design for Fast Protein Motif-Scaffolding with Coupled Flow.

Yufei Huang, Yunshu Liu, Lirong Wu, Haitao Lin, Cheng Tan, Odin Zhang, Zhangyang Gao, Siyuan Li, Zicheng Liu, Yunfan Liu, Tailin Wu, Stan Z. Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

DaCapo: Score Distillation as Stacked Bridge for Fast and High-quality 3D Editing.

Yufei Huang, Bangyan Liao, Yuqi Hu, Haitao Lin, Lirong Wu, Siyuan Li, Cheng Tan, Zicheng Liu, Yunfan Liu, Zelin Zang, Chang Yu, Zhen Lei

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Relation-Aware Equivariant Graph Networks for Epitope-Unknown Antibody Design and Specificity Optimization.

Lirong Wu, Haitao Lin, Yufei Huang, Zhangyang Gao, Cheng Tan, Yunfan Liu, Tailin Wu, Stan Z. Li

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

FoldToken: Learning Protein Language via Vector Quantization and Beyond.

Zhangyang Gao, Cheng Tan, Jue Wang, Yufei Huang, Lirong Wu, Stan Z. Li

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

dyAb: Flow Matching for Flexible Antibody Design with AlphaFold-driven Pre-binding Antigen.

Cheng Tan, Yijie Zhang, Zhangyang Gao, Yufei Huang, Haitao Lin, Lirong Wu, Fandi Wu, Mathieu Blanchette, Stan Z. Li

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions.

Lirong Wu, Haitao Lin, Zihan Liu, Zicheng Liu, Yufei Huang, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., September, 2024

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph.

Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Zicheng Liu, Siyuan Li, Cheng Tan, Zhifeng Gao, Stan Z. Li

CoRR, 2024

GenBench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models.

Zicheng Liu, Jiahui Li, Siyuan Li, Zelin Zang, Cheng Tan, Yufei Huang, Yajing Bai, Stan Z. Li

CoRR, 2024

Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.

Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li

CoRR, 2024

Deep Lead Optimization: Leveraging Generative AI for Structural Modification.

Odin Zhang, Haitao Lin, Hui Zhang, Huifeng Zhao, Yufei Huang, Yuansheng Huang, Dejun Jiang, Chang-Yu Hsieh, Peichen Pan, Tingjun Hou

CoRR, 2024

Deep Geometry Handling and Fragment-wise Molecular 3D Graph Generation.

Odin Zhang, Yufei Huang, Shichen Cheng, Mengyao Yu, Xujun Zhang, Haitao Lin, Yundian Zeng, Mingyang Wang, Zhenxing Wu, Huifeng Zhao, Zaixi Zhang, Chenqing Hua, Yu Kang, Sunliang Cui, Peichen Pan, Chang-Yu Hsieh, Tingjun Hou

CoRR, 2024

Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions.

Rui Sun, Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

CoRR, 2024

Learning Complete Protein Representation by Dynamically Coupling of Sequence and Structure.

Bozhen Hu, Cheng Tan, Jun Xia, Yue Liu, Lirong Wu, Jiangbin Zheng, Yongjie Xu, Yufei Huang, Stan Z. Li

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

UniIF: Unified Molecule Inverse Folding.

Zhangyang Gao, Jue Wang, Cheng Tan, Lirong Wu, Yufei Huang, Siyuan Li, Zhirui Ye, Stan Z. Li

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

Learning to Predict Mutational Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.

Lirong Wu, Yijun Tian, Haitao Lin, Yufei Huang, Siyuan Li, Nitesh V. Chawla, Stan Z. Li

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

PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching.

Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li

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

GeoAB: Towards Realistic Antibody Design and Reliable Affinity Maturation.

Haitao Lin, Lirong Wu, Yufei Huang, Yunfan Liu, Odin Zhang, Yuanqing Zhou, Rui Sun, Stan Z. Li

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

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling.

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Cheng Tan, Jiangbin Zheng, Yufei Huang, Stan Z. Li

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

Re-Dock: Towards Flexible and Realistic Molecular Docking with Diffusion Bridge.

Yufei Huang, Odin Zhang, Lirong Wu, Cheng Tan, Haitao Lin, Zhangyang Gao, Siyuan Li, Stan Z. Li

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

MAPE-PPI: Towards Effective and Efficient Protein-Protein Interaction Prediction via Microenvironment-Aware Protein Embedding.

Lirong Wu, Yijun Tian, Yufei Huang, Siyuan Li, Haitao Lin, Nitesh V. Chawla, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks.

Tianyu Fan, Lirong Wu, Yufei Huang, Haitao Lin, Cheng Tan, Zhangyang Gao, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation.

Lirong Wu, Yunfan Liu, Haitao Lin, Yufei Huang, Stan Z. Li

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction.

Lirong Wu, Yufei Huang, Cheng Tan, Zhangyang Gao, Bozhen Hu, Haitao Lin, Zicheng Liu, Stan Z. Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

Protein 3D Graph Structure Learning for Robust Structure-Based Protein Property Prediction.

Yufei Huang, Siyuan Li, Lirong Wu, Jin Su, Haitao Lin, Odin Zhang, Zihan Liu, Zhangyang Gao, Jiangbin Zheng, Stan Z. Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

MMDesign: Multi-Modality Transfer Learning for Generative Protein Design.

Jiangbin Zheng, Siyuan Li, Yufei Huang, Zhangyang Gao, Cheng Tan, Bozhen Hu, Jun Xia, Ge Wang, Stan Z. Li

CoRR, 2023

Protein 3D Graph Structure Learning for Robust Structure-based Protein Property Prediction.

Yufei Huang, Siyuan Li, Jin Su, Lirong Wu, Odin Zhang, Haitao Lin, Jingqi Qi, Zihan Liu, Zhangyang Gao, Yuyang Liu, Jiangbin Zheng, Stan Z. Li

CoRR, 2023

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration.

Haitao Lin, Yufei Huang, Haotian Zhang, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li

CoRR, 2023

Lightweight Contrastive Protein Structure-Sequence Transformation.

Jiangbin Zheng, Ge Wang, Yufei Huang, Bozhen Hu, Siyuan Li, Cheng Tan, Xinwen Fan, Stan Z. Li

CoRR, 2023

Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy.

Yufei Huang, Lirong Wu, Haitao Lin, Jiangbin Zheng, Ge Wang, Stan Z. Li

CoRR, 2023

A Survey on Protein Representation Learning: Retrospect and Prospect.

Lirong Wu, Yufei Huang, Haitao Lin, Stan Z. Li

CoRR, 2023

Functional-Group-Based Diffusion for Pocket-Specific Molecule Generation and Elaboration.

Haitao Lin, Yufei Huang, Odin Zhang, Yunfan Liu, Lirong Wu, Siyuan Li, Zhiyuan Chen, Stan Z. Li

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

Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs.

Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

Proceedings of the International Conference on Machine Learning, 2023

Extracting Low-/High- Frequency Knowledge from Graph Neural Networks and Injecting It into MLPs: An Effective GNN-to-MLP Distillation Framework.

Lirong Wu, Haitao Lin, Yufei Huang, Tianyu Fan, Stan Z. Li

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Non-equispaced Fourier Neural Solvers for PDEs.

Haitao Lin, Lirong Wu, Yongjie Xu, Yufei Huang, Siyuan Li, Guojiang Zhao, Stan Z. Li

CoRR, 2022

Protein Language Models and Structure Prediction: Connection and Progression.

Bozhen Hu, Jun Xia, Jiangbin Zheng, Cheng Tan, Yufei Huang, Yongjie Xu, Stan Z. Li

CoRR, 2022

DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding.

Haitao Lin, Yufei Huang, Meng Liu, Xuanjing Li, Shuiwang Ji, Stan Z. Li

CoRR, 2022

Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation.

Lirong Wu, Yufei Huang, Haitao Lin, Zicheng Liu, Tianyu Fan, Stan Z. Li

CoRR, 2022

Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks.

Lirong Wu, Haitao Lin, Yufei Huang, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings.

Jiangbin Zheng, Yile Wang, Ge Wang, Jun Xia, Yufei Huang, Guojiang Zhao, Yue Zhang, Stan Z. Li

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022