Binghui Xie

According to our database, Binghui Xie authored at least 14 papers between 2020 and 2026.

Collaborative distances:

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

2026

Predicting drug responses of unseen cell types through transfer learning with foundation models.

Yixuan Wang, Xinyuan Liu, Yimin Fan, Binghui Xie, James Cheng, Kam Chung Wong, Pak Hang Peter Cheung, Irwin King, Yu Li

Nat. Comput. Sci., January, 2026

2025

Federated Domain Generalization with Decision Insight Matrix.

Tianchi Liao, Binghui Xie, Lele Fu, Sheng Huang, Bowen Deng, Chuan Chen, Zibin Zheng

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

2024

HORSE: Hierarchical Representation for Large-Scale Neural Subset Selection.

Binghui Xie, Yixuan Wang, Yongqiang Chen, Kaiwen Zhou, Yu Li, Wei Meng, James Cheng

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

Enhancing Neural Subset Selection: Integrating Background Information into Set Representations.

Binghui Xie, Yatao Bian, Kaiwen Zhou, Yongqiang Chen, Peilin Zhao, Bo Han, Wei Meng, James Cheng

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Enhancing Evolving Domain Generalization through Dynamic Latent Representations.

Binghui Xie, Yongqiang Chen, Jiaqi Wang, Kaiwen Zhou, Bo Han, Wei Meng, James Cheng

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

2023

Positional Information Matters for Invariant In-Context Learning: A Case Study of Simple Function Classes.

Yongqiang Chen, Binghui Xie, Kaiwen Zhou, Bo Han, Yatao Bian, James Cheng

CoRR, 2023

Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Yongqiang Chen, Yatao Bian, Kaiwen Zhou, Binghui Xie, Bo Han, James Cheng

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

Pareto Invariant Risk Minimization: Towards Mitigating the Optimization Dilemma in Out-of-Distribution Generalization.

Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Bingzhe Wu, Yonggang Zhang, Kaili Ma, Han Yang, Peilin Zhao, Bo Han, James Cheng

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Pareto Invariant Risk Minimization.

Yongqiang Chen, Kaiwen Zhou, Yatao Bian, Binghui Xie, Kaili Ma, Yonggang Zhang, Han Yang, Bo Han, James Cheng

CoRR, 2022

An Adaptive Incremental Gradient Method With Support for Non-Euclidean Norms.

Binghui Xie, Chenhan Jin, Kaiwen Zhou, James Cheng, Wei Meng

CoRR, 2022

Invariance Principle Meets Out-of-Distribution Generalization on Graphs.

Yongqiang Chen, Yonggang Zhang, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

CoRR, 2022

Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs.

Yongqiang Chen, Yonggang Zhang, Yatao Bian, Han Yang, Kaili Ma, Binghui Xie, Tongliang Liu, Bo Han, James Cheng

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

Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin Attack.

Ruize Gao, Jiongxiao Wang, Kaiwen Zhou, Feng Liu, Binghui Xie, Gang Niu, Bo Han, James Cheng

Proceedings of the International Conference on Machine Learning, 2022

2020

Second Order Enhanced Multi-glimpse Attention in Visual Question Answering.

Qiang Sun, Binghui Xie, Yanwei Fu

Proceedings of the Computer Vision - ACCV 2020 - 15th Asian Conference on Computer Vision, Kyoto, Japan, November 30, 2020