Scaling Cheap Synthetic Pretraining Improves Indoor Radio-Map Prediction

cs.LG, cs.AI

Submitted: 2026-10-13

Updated: 2026-10-13

Comments: Accepted at NeurIPS 2026. This research was in part sponsored by the HESC MESCS RA grant No. 22rl-052 (DISTAL), and by the NATO Science for Peace and Security Programme under grant ID G9270 (OASIS)

Code: https://github.com/xoren22/cheap-synth-pretrain-neurips26

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
• Scaling Laws for Neural Language Models

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