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Beyond Solver Verdicts: Generative Reward Models for Autoformalization

Singh, Vikash et al.
arXiv (OAI Expanded) · Papers
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computation-and-languagemachine-learning
Neurosymbolic systems rely on mathematical solvers to guarantee reasoning correctness, yet solvers are fundamentally blind to whether a formal translation maintains strict reference-equivalence to a designated formalization. We formalize this vulnerability as Verdict-Preserving-Unfaithfulness (VPU):
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