Hilbert-Geo: Solving Solid Geometric Problems by Neural-Symbolic Reasoning 文章

ArXiv CS.CV2026-05-29NEWSen作者: Ruoran Xu, Haoyu Cheng, Bin Dong, Qiufeng Wang

摘要

arXiv:2605.16385v2 Announce Type: replace Abstract: Geometric problem solving, as a typical multimodal reasoning problem, has attracted much attention and made great progress recently, however most of works focus on plane geometry while usually fail in solid geometry due to 3D spatial diagrams and complex reasoning. To bridge this gap, we introduce Hilbert-Geo, the first unified formal language framework for solid geometry, including an extensive predicate library and a dedicated theorem bank. Based on this framework, we propose a Parse2Reason method containing two steps of first parsing then reasoning. In the parsing step, we utilize conditional description language (CDL), a formalized language composed of predicates specifically designed to construct geometric conditions, to represent both problem description (natural text) and solid diagrams (visual image).