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Spatial disparities of self-reported COVID-19 cases and influencing factors in Wuhan, China

G. Xu, Y. Jiang, S. Wang, K. Qin, J. Ding, Y. Liu, B. Lu

Sustainable Cities and Society, 2022

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Map Retrieval Intention Formalization and Recognition by Considering Geographic Semantics

Z. Gui, X. Hu, X. Liu, Z. Ling, Y. Jiang, H. Wu

Journal of Geo-information Science, 2023

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Open GIS — Chapter 10: Desktop-based Mapping and Visualization Tools; Chapter 11: Web-based Mapping and Visualization Packages

Y. Jiang, contributing author · J. Xia, Q. Huang, Z. Gui, W. Tu (Eds.)

Open GIS (Springer International Publishing), 2024

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Map retrieval intention recognition based on relevance feedback and geographic semantic guidance: For better understanding user retrieval demands

Z. Gui, X. Liu, A. Zhao, Y. Jiang, Z. Ling, X. Hu, F. Li, Z. Yang, H. Wu, S. Zhao

Information Processing & Management, 2024

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Beyond Spatial Proximity: A Temporal Accessibility Index for Equitable Nature Access in Bavaria’s Hiking Trails

Y. Jiang, P. Luo

Abstracts of the ICA, 2025

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Lost in Aggregation: A Multi-Scale Diagnostic Benchmark for LLM Spatial Navigation

Y. Jiang, P. Luo, L. Meng

arXiv preprint arXiv:2606.22219, 2026

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Constructing coherent spatial memory in LLM agents through graph rectification

P. Zhang, X. Chen, Y. Feng, Y. Jiang, L. Meng

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (ACL 2026), 2026

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Explaining the urban mechanisms behind OpenStreetMap updates: Evidence from 88 German cities

C. Chen, Y. Jiang, Y. Feng, Y. Liu, L. Meng

Computers, Environment and Urban Systems, 2026

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Beyond Spatial Proximity: A Temporal Accessibility Index for Equitable Nature Access in Bavaria’s Hiking Trails

Published: August 17, 2025

Physical distance alone is a poor measure of who can actually reach nature. This talk presented a temporal accessibility index for Bavaria’s hiking trails that accounts for how reachable trails are by public transport, and what that implies for equitable access to nature.

DTN Annual Forum 2025

Published: September 10, 2025

Where Do LLMs Get Lost? A Multi-Scale Diagnostic Benchmark for Spatial Navigation

Published: May 11, 2026

The poster asks which spatial representations best support LLM navigation, where LLMs fail across spatial scales, and what levels of spatial decision-making should be delegated to an LLM in a hybrid navigation agent.

Lost in Aggregation: A Multi-Scale Diagnostic Benchmark for LLM Spatial Navigation

Published: June 11, 2026

Large language models act as planners in tasks with inherent spatial structure, yet stay brittle at sequential spatial reasoning. Rather than asking whether they fail at navigation, the poster asks where in the spatial-cognition pipeline they get lost — decomposing maze navigation into Fine (local passability), Meso (junction topology) and Macro (goal orientation) levels across 1,050 mazes. First errors concentrate on Meso junction choices (59%) and Fine perception (39%), with global heading almost never at fault (1%).