Local-only spatial training yields a recoverable global coordinate map

Xia et al. continually pretrain Qwen2.5-0.5B on synthetic relational and trajectory descriptions of a simulated 100x100 city that only ever describe local relationships between nearby points [xia-etal-2025-can-llms-learn-to-map-the-world] A probe on last hidden states recovers absolute (x,y) coordinates at R^2=1.00 (vs -0.01/-0.10 untrained), an emergent global coordinate map from purely local signal [xia-etal-2025-can-llms-learn-to-map-the-world] Independently of the probe, latent-vector distances and angles show high Spearman/Pearson correlation with true geographic distances and angles [xia-etal-2025-can-llms-learn-to-map-the-world] A compositional probe recovers pairwise distance (MAE 0.85) and azimuth (3.49 degrees) at R^2 1.00/0.98; no activation-level intervention is performed [xia-etal-2025-can-llms-learn-to-map-the-world]