BiNSGPS: Geometry Problem Solving via Bidirectional Neuro-Symbolic Interaction

• URL: http://arxiv.org/abs/2606.04648v1
• Date: Wed, 03 Jun 2026 09:18:37 GMT
• Title: BiNSGPS: Geometry Problem Solving via Bidirectional Neuro-Symbolic Interaction
• Abstract summary: BiNSGPS is a framework that establishes Bidirectional Neuro-Symbolic Interaction between a MLLM Adviser and a solver.<n> MLLM Adviser actively incorporates feedback from the symbolic solver to dynamically rectify inconsistent formal representations.
• Score: 45.32907555157728
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Geometry problem solving poses distinct challenges in artificial intelligence. Existing approaches typically fall into two paradigms: symbolic methods, which exhibit limited adaptability, and neural methods, which are prone to hallucinations. Recent neuro-symbolic hybrids predominantly rely on a unidirectional pipeline where neural outputs are fed into solvers without feedback, making system brittle to early-stage errors. To break this unidirectional bottleneck, we propose BiNSGPS, a framework that establishes Bidirectional Neuro-Symbolic Interaction (BiNS) between a MLLM Adviser and a Symbolic Solver. MLLM Adviser actively incorporates feedback from the symbolic solver to dynamically rectify inconsistent formal representations or propose auxiliary hypotheses, resolving symbolic conflicts and facilitating complex deductions.

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