1 citations · 1 across the 7 of their papers we have counts for
10 papers
Learning Dynamic Belief Graphs for Theory-of-mind Reasoning
Ruxiao Chen, Xilei Zhao, Thomas J. Cova +2
Theory of Mind (ToM) reasoning with Large Language Models (LLMs) requires inferring how people's implicit, evolving beliefs shape what they seek and how they act under uncertainty…
Multi-Task Anti-Causal Learning for Reconstructing Urban Events from Residents' Reports
Liangkai Zhou, Susu Xu, Shuqi Zhong +1
Many real-world machine learning tasks are anti-causal: they require inferring latent causes from observed effects. In practice, we often face multiple related tasks where part of…
Persona-aware and Explainable Bikeability Assessment: A Vision-Language Model Approach
Yilong Dai, Ziyi Wang, Chenguang Wang +4
Bikeability assessment is essential for advancing sustainable urban transportation and creating cyclist-friendly cities, and it requires incorporating users' perceptions of safety…
From Image Generation to Infrastructure Design: a Multi-agent Pipeline for Street Design Generation
Chenguang Wang, Xiang Yan, Yilong Dai +2
Realistic visual renderings of street-design scenarios are essential for public engagement in active transportation planning. Traditional approaches are labor-intensive, hindering…
Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning
Yuran Sun, Susu Xu, Chenguang Wang +1
Big trajectory data hold great promise for human mobility analysis, but their utility is often constrained by the absence of critical traveler attributes, particularly sociodemogra…
Multi-resolution Score-Based Variational Graphical Diffusion for Causal Disaster System Modeling and Inference
Xuechun Li, Shan Gao, Susu Xu
Complex systems with intricate causal dependencies challenge accurate prediction. Effective modeling requires precise physical process representation, integration of interdependent…