Hao Dong

According to our database, Hao Dong authored at least 25 papers between 2021 and 2026.

Collaborative distances:

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

2026

Advances in Multimodal Adaptation and Generalization: From Traditional Approaches to Foundation Models.

Hao Dong, Moru Liu, Kaiyang Zhou, Eleni N. Chatzi, Juho Kannala, Cyrill Stachniss, Olga Fink

IEEE Trans. Pattern Anal. Mach. Intell., May, 2026

Are We Making Progress in Multimodal Domain Generalization? A Comprehensive Benchmark Study.

Hao Dong, Hongzhao Li, Shupan Li, Muhammad Haris Khan, Eleni N. Chatzi, Olga Fink

CoRR, May, 2026

Adaptive Confidence Regularization for Multimodal Failure Detection.

Moru Liu, Hao Dong, Olga Fink, Mario Trapp

CoRR, March, 2026

Towards Multimodal Domain Generalization with Few Labels.

Hongzhao Li, Hao Dong, Hualei Wan, Shupan Li, Mingliang Xu, Muhammad Haris Khan

CoRR, February, 2026

Multimodal Learning for Arcing Detection in Pantograph-Catenary Systems.

Hao Dong, Eleni N. Chatzi, Olga Fink

CoRR, February, 2026

From physics to machine learning and back: Part I - Learning with inductive biases in prognostics and health management (PHM).

Olga Fink, Vinay Sharma, Ismail Nejjar, Leandro Von Krannichfeldt, Sergei Garmaev, Zepeng Zhang, Amaury Wei, Gaëtan Frusque, Florent Forest, Mengjie Zhao, Chi-Ching Hsu, Keivan Faghih Niresi, Han Sun, Hao Dong, Chenghao Xu, Raffael Theiler, Arthur Bizzi, Kevin Steiner

Reliab. Eng. Syst. Saf., 2026

From physics to machine learning and back: Part II - Learning and observational bias in prognostics and health management (PHM).

Olga Fink, Ismail Nejjar, Vinay Sharma, Keivan Faghih Niresi, Han Sun, Hao Dong, Chenghao Xu, Amaury Wei, Arthur Bizzi, Raffael Theiler, Yuan Tian, Leandro Von Krannichfeldt, Zhan Ma, Sergei Garmaev, Zepeng Zhang, Mengjie Zhao, Kevin Steiner, Yusuf Kesmen

Reliab. Eng. Syst. Saf., 2026

2025

From Physics to Machine Learning and Back: Part II - Learning and Observational Bias in PHM.

Olga Fink, Ismail Nejjar, Vinay Sharma, Keivan Faghih Niresi, Han Sun, Hao Dong, Chenghao Xu, Amaury Wei, Arthur Bizzi, Raffael Theiler, Yuan Tian, Leandro Von Krannichfeldt, Zhan Ma, Sergei Garmaev, Zepeng Zhang, Mengjie Zhao

CoRR, September, 2025

Adapting Vision-Language Models Without Labels: A Comprehensive Survey.

Hao Dong, Lijun Sheng, Jian Liang, Ran He, Eleni N. Chatzi, Olga Fink

CoRR, August, 2025

NNG-Mix: Improving Semi-Supervised Anomaly Detection With Pseudo-Anomaly Generation.

Hao Dong, Gaëtan Frusque, Yue Zhao, Eleni N. Chatzi, Olga Fink

IEEE Trans. Neural Networks Learn. Syst., June, 2025

To Trust Or Not To Trust Your Vision-Language Model's Prediction.

Hao Dong, Moru Liu, Jian Liang, Eleni N. Chatzi, Olga Fink

CoRR, May, 2025

Recall and Refine: A Simple but Effective Source-free Open- set Domain Adaptation Framework.

Ismail Nejjar, Hao Dong, Olga Fink

Trans. Mach. Learn. Res., 2025

Extremely Simple Multimodal Outlier Synthesis for Out-of-Distribution Detection and Segmentation.

Moru Liu, Hao Dong, Jessica Kelly, Olga Fink, Mario Trapp

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization.

Hao Dong, Eleni N. Chatzi, Olga Fink

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Unseen Visual Anomaly Generation.

Han Sun, Yunkang Cao, Hao Dong, Olga Fink

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

DPU: Dynamic Prototype Updating for Multimodal Out-of-Distribution Detection.

Shawn Li, Huixian Gong, Hao Dong, Tiankai Yang, Zhengzhong Tu, Yue Zhao

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

2024

Sym-Q: Adaptive Symbolic Regression via Sequential Decision-Making.

Yuan Tian, Wenqi Zhou, Hao Dong, David S. Kammer, Olga Fink

CoRR, 2024

MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities.

Hao Dong, Yue Zhao, Eleni N. Chatzi, Olga Fink

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

SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation.

Hao Dong, Weihao Gu, Xianjing Zhang, Jintao Xu, Rui Ai, Huimin Lu, Juho Kannala, Xieyuanli Chen

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Towards Multimodal Open-Set Domain Generalization and Adaptation Through Self-supervision.

Hao Dong, Eleni N. Chatzi, Olga Fink

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Online pole segmentation on range images for long-term LiDAR localization in urban environments.

Hao Dong, Xieyuanli Chen, Simo Särkkä, Cyrill Stachniss

Robotics Auton. Syst., 2023

SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization.

Hao Dong, Ismail Nejjar, Han Sun, Eleni N. Chatzi, Olga Fink

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

Learning-Based Dimensionality Reduction for Computing Compact and Effective Local Feature Descriptors.

Hao Dong, Xieyuanli Chen, Mihai Dusmanu, Viktor Larsson, Marc Pollefeys, Cyrill Stachniss

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022

SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation and Prediction.

Hao Dong, Xianjing Zhang, Xuan Jiang, Jun Zhang, Jintao Xu, Rui Ai, Weihao Gu, Huimin Lu, Juho Kannala, Xieyuanli Chen

CoRR, 2022

2021

Online Range Image-based Pole Extractor for Long-term LiDAR Localization in Urban Environments.

Hao Dong, Xieyuanli Chen, Cyrill Stachniss

Proceedings of the 10th European Conference on Mobile Robots, 2021