TREAT: Evaluating Access to Formal Knowledge across Equivalent Mathematical Representations
New benchmark reveals that AI models struggle to recognize identical mathematical theorems when expressed differently.
AI systems increasingly operate between flexible input representations and formal objects used by downstream tools. A key challenge is recognizing when an unfamiliar formulation denotes a known formal object. We study this challenge through theorem recognition: given an equivalen...
ArXiv CS.AI
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The TREAT benchmark highlights a critical vulnerability in current LLMs where mathematical knowledge is tied to specific syntax rather than conceptual understanding. This fragility suggests that improving representation-robustness is essential for scaling AI in fields requiring high-precision reasoning like formal verification and scientific research.
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