[2504.15780] TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving

Computer Science > Artificial Intelligence arXiv:2504.15780 (cs) [Submitted on 22 Apr 2025 (v1), last revised 26 Mar 2026 (this version, v3)] Title:TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving Authors:Daocheng Fu, Jianlong Chen, Renqiu Xia, Zijun Chen, Qi Liu, Yuan Feng, Hongbin Zhou, Renrui Zhang, Shiyang Feng, Peng Gao, Hongyuan Zha, Junchi Yan, Botian Shi, Yu Qiao, Bo Zhang View a PDF of the paper titled TrustGeoGen: Formal-Verified Data Engine for Trustworthy Multi-modal Geometric Problem Solving, by Daocheng Fu and 14 other authors View PDF HTML (experimental) Abstract:Geometric problem solving (GPS) requires precise multimodal understanding and rigorous, step-by-step logical reasoning. However, developing capable Multimodal Large Language Models (MLLMs) for GPS is heavily bottlenecked by the scarcity of high-quality, verifiable data. Existing data acquisition paradigms either suffer from modality incompleteness and unverified logical gaps ("leaps-of-faith"), or rely on formal engines that generate rigid, structurally homogeneous data, failing to produce high-difficulty problems or foster genuine natural-language reasoning. To overcome these limitations, we introduce TrustGeoGen, an autonomous and formalized geometric data generation engine. TrustGeoGen strictly guarantees reasoning trustworthiness through formal verification while generating multimodally integrated data, including premises, visual diagrams, and soluti...