AISep 16, 2025
Stochastic Streets: A Walk Through Random LLM Address Generation in four European Cities
Tairan Fu, David Campo-Nazareno, Javier Coronado-Blázquez, Javier Conde, Pedro Reviriego, Fabrizio Lombardi
arXiv:2509.12914v1h-index: 9Computer
Originality Synthesis-oriented
AI Analysis
This addresses a niche problem for researchers or developers needing synthetic address data, but it is incremental as it applies existing LLM capabilities to a new, specific task.
The paper investigates whether large language models can generate random street addresses for four European cities, finding they can produce plausible addresses but with varying accuracy across cities.
Large Language Models (LLMs) are capable of solving complex math problems or answer difficult questions on almost any topic, but can they generate random street addresses for European cities?