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20232026
most citedModal Decomposition and Identification for a Population of Structures Using Physics-Informed Graph Neural Networks and Transformers

7 citations · 15 across the 8 of their papers we have counts for

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cs.CV2026

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

Hao Dong, Hongzhao Li, Shupan Li +3

Despite the growing popularity of Multimodal Domain Generalization (MMDG) for enhancing model robustness, it remains unclear whether reported performance gains reflect genuine algo…

cs.CV2026

Multimodal Learning for Arcing Detection in Pantograph-Catenary Systems

Hao Dong, Eleni Chatzi, Olga Fink

The pantograph-catenary interface is essential for ensuring uninterrupted and reliable power delivery in electrified rail systems. However, electrical arcing at this interface pose…

cs.CV2025

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

Hao Dong, Moru Liu, Jian Liang +2

Vision-Language Models (VLMs) have demonstrated strong capabilities in aligning visual and textual modalities, enabling a wide range of applications in multimodal understanding and…

cs.CV2025

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

Hao Dong, Eleni Chatzi, Olga Fink

Test-time adaptation (TTA) has demonstrated significant potential in addressing distribution shifts between training and testing data. Open-set test-time adaptation (OSTTA) aims to…

cs.CV2025

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

Hao Dong, Moru Liu, Kaiyang Zhou +4

In real-world scenarios, achieving domain adaptation and generalization poses significant challenges, as models must adapt to or generalize across unknown target distributions. Ext…

cs.CV2024

Towards Multimodal Open-Set Domain Generalization and Adaptation through Self-supervision

Hao Dong, Eleni Chatzi, Olga Fink

The task of open-set domain generalization (OSDG) involves recognizing novel classes within unseen domains, which becomes more challenging with multiple modalities as input. Existi…