MathAtlas: New Benchmark for Graduate-Level Autoformalization
๐กFirst benchmark for graduate-level math autoformalization; exposes critical failures in current SOTA reasoning models.
โก 30-Second TL;DR
What Changed
Contains 52k theorems, definitions, and proofs from 103 graduate textbooks.
Why It Matters
This benchmark exposes the limitations of current LLMs in handling deep, structured mathematical reasoning. It will likely drive research into more robust, dependency-aware architectures for formal mathematics.
What To Do Next
Download the MathAtlas dataset from the arXiv repository to stress-test your model's reasoning capabilities on complex, multi-step mathematical proofs.
Key Points
- โขContains 52k theorems, definitions, and proofs from 103 graduate textbooks.
- โขFeatures a dependency graph with 178k relations for dependency-aware evaluation.
- โขReveals significant performance degradation in SOTA models as dependency depth increases.
- โขProvides a challenging testbed for autoformalization with low baseline correctness scores.
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Original source: ArXiv AI โ