SGA: Plug&Play Geometric Verification for Educational Video Synthesis
Researchers introduce the Symbolic Geometric Agent (SGA), a plug-and-play module designed to enhance spatial correctness in LLM-generated code for educational animations. SGA intercepts code, extracts symbolic scene graphs, and refines outputs when spatial conflicts are detected, without requiring full rendering. The team also proposes the Manim Visual Quality Score (MVQS) as a rendering-free metric for spatial integrity. Experiments on the MMMC-Code benchmark show SGA achieves a peak MVQS of 73.11, representing a 16.1% relative improvement over the baseline.
Why it matters: This work offers a practical solution for improving the spatial quality of automatically generated educational animations, addressing a key challenge in AI-driven content creation.
Full story at: arXiv Multiagent Systems ↗