works on

From the 1 of 5 linked papers with an AI index.

activity
20242026
most citedGeospatial Representation Learning: A Survey from Deep Learning to The LLM Era

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling

Xixuan Hao, Yutian Jiang, Jiabo Liu +4

The paper introduces UrbanAgent, a multi‑agent system that treats urban region profiling as a reasoning task, using separate agents for each data modality and tool‑augmented eviden…

cs.CV20261 cited

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…

cs.AI2025

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…

cs.AI2025

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…

cs.AI2024

GraphAgent: Agentic Graph Language Assistant

Yuhao Yang, Jiabin Tang, Lianghao Xia +3

Real-world data is represented in both structured (e.g., graph connections) and unstructured (e.g., textual, visual information) formats, encompassing complex relationships that in…