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FormInv: A Measurement Protocol for Semantic Invariance in Mathematical Reasoning Benchmarks

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Computer Science > Machine Learning

arXiv:2605.29001 (cs)
[Submitted on 27 May 2026]

Title:FormInv: A Measurement Protocol for Semantic Invariance in Mathematical Reasoning Benchmarks

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Abstract:A paraphrase-quality audit of MathCheck (ICLR 2025) detected 4 semantically incorrect paraphrases in 129 groups (3.1%); removing them drops GPT-4o from rank 2 to rank 4 and elevates Claude Haiku and DeepSeek V3 above it; these ranking changes are invisible to any single-model evaluation. Cross-model unanimity found these errors automatically (>= 3/4 models for MathCheck; >= 6/9 for our primary evaluation) for under $10; in our own dataset the same protocol found that 47% of auto-generated connective-variation paraphrases were semantically incorrect. That flaw compounds a deeper measurement gap: Claude Haiku 4.5 achieves 86% accuracy yet SCR=50%, meaning half its theorems are answered differently under semantically equivalent restatements, while aggregate accuracy across 9 models spans only 86-96% yet Semantic Consistency Rates (SCR) span 50-82% -- a 32-point gap invisible to standard benchmarks. Formally, for any target ranking over 9 frontier models there exists a weighting over paraphrase families that realizes it (No-Free-Benchmark corollary), because no model Pareto-dominates all families -- so benchmark designers who select families are implicitly choosing which model wins. FormInv supplies the audit protocol (replicated on external benchmarks at 100% recall), SCR and per-theorem Cochran's Q as primary invariance measures evaluated on 9 models across 366-811 items (on Lean4-verified theorems), and FormInvSelector for regime-aware model selection.
Comments: 18 pages, 3 figures. Under review for the 3rd AI for Math Workshop (AI4Math), ICML 2026
Subjects: Machine Learning (cs.LG); Artificial Intelligence (cs.AI)
Cite as: arXiv:2605.29001 [cs.LG]
  (or arXiv:2605.29001v1 [cs.LG] for this version)
  https://doi.org/10.48550/arXiv.2605.29001
arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Noel Thomas [view email]
[v1] Wed, 27 May 2026 18:59:18 UTC (84 KB)
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