mlsanityData to 7 Oct 2026

City Editing: Hierarchical Agentic Execution for Dependency-Aware Urban Geospatial Modification

arXiv 2602.19326 ↗First posted 22 Feb 2026cs.MA cs.AIcited by 1

On the map: LLM agents and tool use → Multimodal and embodied agents

Abstract (arXiv)

Urban renewal requires incremental modifications to existing geospatial plans, yet manually updating complex layouts under spatial constraints is labor-intensive and error-prone. To tackle this, we propose CEAE, a hierarchical agentic framework that formulates urban renewal as machine-executable GeoJSON editing from natural-language instructions. CEAE decomposes instructions into hierarchical geometric intents, executing edits from coarse to fine while preserving spatial consistency through a self-reflective execution-validation loop. Experimental results show that CEAE outperforms baselines in execution validity, robustness, and geometric accuracy.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Placed in Multimodal and embodied agents, one of 16 directions in LLM agents and tool use. Builds on 15 of its 27 references that are in the map. First posted on arXiv 22 Feb 2026.

Builds on

15 of 27 references.

Closest ancestors · 2

Same direction, newest first

  1. 2025Towards Urban Planing AI Agent in the Age of Agentic AI19 Jul
  2. 2024Agent AI: Surveying the Horizons of Multimodal Interaction7 Jan

Other references · 13

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2019PyTorch: An Imperative Style, High-Performance Deep Learning Librarycited by 20,160
  3. 2023GPT-4 Technical Reportcited by 18,132
  4. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  5. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,201
  6. 2025SkillWeaver: Web Agents can Self-Improve by Discovering and Honing Skillscited by 174
  7. 2024Large Language Model for Participatory Urban Planningcited by 40
  8. 2020Reimagining City Configuration: Automated Urban Planning via Adversarial Learningcited by 18
  9. 2022Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planningcited by 15
  10. 2021Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planningcited by 13
  11. 2021Automated Urban Planning for Reimagining City Configuration via Adversarial Learning: Quantification, Generation, and Evaluationcited by 11
  12. 2023Generative AI Meets Future Cities: Towards an Era of Autonomous Urban Intelligencecited by 8
1 more
  1. 2023Dual-stage Flows-based Generative Modeling for Traceable Urban Planningcited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026AgentOS: From Application Silos to a Natural Language-Driven Data Ecosystemcited by 3

Similar, not cited

Close in wording, no citation either way

  1. 2025MapAgent: A Hierarchical Agent for Geospatial Reasoning with Dynamic Map Tool Integration
  2. 2026Imagine a City: CityGenAgent for Procedural 3D City Generation
  3. 2025GeoJSON Agents:A Multi-Agent LLM Architecture for Geospatial Analysis-Function Calling vs Code Generation
  4. 2026WorldClaw: Agentic 3D Open-World Generation at Scale
  5. 2026UrbanAgent: A Tool-Augmented Agent for Cross-System Urban Tasks
  6. 2026GeoAI Agency Primitives
  7. 2026GeoAgentBench: A Dynamic Execution Benchmark for Tool-Augmented Agents in Spatial Analysis
  8. 2026ANASSA: An Agentic AI Orchestration Framework for Spatial Intelligence