arXiv — cs.AI preprintsInternational9 October 2026
Self-Evolving Spatial Reasoning in Vision Language Models via Geometric Logic Consistency
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arXiv:2605.18162v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have made striking progress, yet their spatial reasoning remains fragile. Models that answer an original input correctly can still fail under valid transformations with predictable answer mappings, revealing a gap between instance-level correctness and robust spatial reasoning. To address this, we propose Spatial Alignment via Geometric Evolution (SAGE), a self-evolving framework that improves robust spatial reasoning through geometric and linguistic duality operations. SAGE incorporates duality consistency
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