Spatial training lifts a VLM 27.63 points

Fine-tuning Qwen3-VL-8B on GST-Train raised its global-spatial-awareness score from 25.89 to 53.52, a 27.63-point gain, in the GST-Bench paper. The 2,762-question benchmark forces 22 vision-language models to reconstruct long video trajectories from novel viewpoints; the strongest zero-shot system scored 42.68 against 79.08 for humans. Robotics teams should file the result beside World Labs’ simulation-first robot-testing funnel: targeted spatial curricula may beat a larger zero-shot model, but synthetic-video gains still need validation against noisy physical sensors.