# EVIDENCECONNECT

Training data for multimodal perception no longer has to be built task by task. Spatial perception and long-context understanding previously relied on costly annotation, so EVIDENCECONNECT instead picks 3 to 7 related regions in one image and synthesizes multiple-choice questions that require comparing, aggregating or chaining evidence from zoomed views, then trains base models with RLVR. ZwZ2-4B rises from 37.43 to 45.26 on ViewSpatial-Bench and from 60.08 to 70.08 on MileBench, with its 25-benchmark average moving from 49.41 to 54.79.

Training data for multimodal perception no longer has to be built task by task. Spatial perception and long-context understanding previously relied on costly annotation, so EVIDENCECONNECT instead picks 3 to 7 related regions in one image and synthesizes multiple-choice questions that require comparing, aggregating or chaining evidence from zoomed views, then trains base models with RLVR. ZwZ2-4B rises from 37.43 to 45.26 on ViewSpatial-Bench and from 60.08 to 70.08 on MileBench, with its 25-benchmark average moving from 49.41 to 54.79.