140 citations · 328 across the 38 of their papers we have counts for
5 papers · 1 filter
Sparkle: Mastering Basic Spatial Capabilities in Vision Language Models Elicits Generalization to Spatial Reasoning
Yihong Tang, Ao Qu, Zhaokai Wang +7
Vision language models (VLMs) perform well on many tasks but often fail at spatial reasoning, which is essential for navigation and interaction with physical environments. Many spa…
GETS: Ensemble Temperature Scaling for Calibration in Graph Neural Networks
Dingyi Zhuang, Chonghe Jiang, Yunhan Zheng +2
Graph Neural Networks deliver strong classification results but often suffer from poor calibration performance, leading to overconfidence or underconfidence. This is particularly p…
SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks
Dingyi Zhuang, Yuheng Bu, Guang Wang +2
Quantifying uncertainty is crucial for robust and reliable predictions. However, existing spatiotemporal deep learning mostly focuses on deterministic prediction, overlooking the i…
Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network
Dingyi Zhuang, Qingyi Wang, Yunhan Zheng +4
Transportation mode share analysis is important to various real-world transportation tasks as it helps researchers understand the travel behaviors and choices of passengers. A typi…
Deep neural networks for choice analysis: Enhancing behavioral regularity with gradient regularization
Siqi Feng, Rui Yao, Stephane Hess +4
Deep neural networks (DNNs) frequently present behaviorally irregular patterns, significantly limiting their practical potentials and theoretical validity in travel behavior modeli…