"Give me five papers with code demonstrating the state of the art of machine learning which uses geospatial data (e.g. GeoJSON) as both input and output."
There is no such state of the art. My hand-wavey understanding is that GIS data is non-continuous, which makes it useless for transformers, and also contextual, which makes it useless for anything else. Will defer to actual ML people for better explanations.
Point is, LLMs invariably give five papers with code that don't actually exist - it's a guaranteed hallucination.
Phind was able to give me five links that do in fact exist, as well as contextual information as to why these five links were not papers with code doing ML with GIS data. This is by far the best answer to this question from an LLM I've received yet.