2 citations · 3 across the 8 of their papers we have counts for
5 papers · 1 filter
AgentSense: LLMs Empower Generalizable and Explainable Web-Based Participatory Urban Sensing
Xusen Guo, Mingxing Peng, Xixuan Hao +4
Web-based participatory urban sensing has emerged as a vital approach for modern urban management by leveraging mobile individuals as distributed sensors. However, existing urban s…
Urban-R1: Reinforced MLLMs Mitigate Geospatial Biases for Urban General Intelligence
Qiongyan Wang, Xingchen Zou, Yutian Jiang +4
Rapid urbanization intensifies the demand for Urban General Intelligence (UGI), referring to AI systems that can understand and reason about complex urban environments. Recent stud…
MR.Rec: Synergizing Memory and Reasoning for Personalized Recommendation Assistant with LLMs
Jiani Huang, Xingchen Zou, Lianghao Xia +1
The application of Large Language Models (LLMs) in recommender systems faces key challenges in delivering deep personalization and intelligent reasoning, especially for interactive…
Traffic-R1: Reinforced LLMs Bring Human-Like Reasoning to Traffic Signal Control Systems
Xingchen Zou, Yuhao Yang, Zheng Chen +4
We introduce Traffic-R1, a 3B-parameter foundation model with human-like reasoning for Traffic signal control (TSC), developed via self-exploration and iterative reinforcement of L…
Geospatial Representation Learning: A Survey from Deep Learning to The LLM Era
Xixuan Hao, Yutian Jiang, Xingchen Zou +6
The ability to transform location-centric geospatial data into meaningful computational representations has become fundamental to modern spatial analysis and decision-making. Geosp…