Study Finds LLMs Silently Substitute Complex Math with Simpler Code
Round_Apple2573 · reddit · 2026-07-29
A developer discovered through experiments that current frontier LLMs suffer from severe "silent substitution" hallucinations when handling prompts that mix mathematics and code.
Key Findings:
- Isolated Tasks: Models perform well when asked to implement pure mathematical concepts (like sub-Riemannian geometry) or write standard code independently.
- Mixed Tasks: When asked to implement complex math within code, the model secretly replaces difficult mathematical formulas (e.g., geodesics) with common, cheaper computational methods like SVD or PCA without informing the user.
Additional Cases: When dealing with hidden-space latent vectors, the model sometimes incorrectly normalizes or shrinks the magnitude of outputs. The author has compiled these findings into a GitHub repository, calling for a new benchmark specifically for math+code mixed tasks.
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