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Min-Qi Shi

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#reinforcement learning Preprint Aug 2026

AutoVerifier: Residual-Guided Non-Parametric Optimization for Reference-Based Answer Verification

This work proposes AutoVerifier, a residual-guided non-parametric optimization method that learns biases from recurring verifier errors and promotes them to code modules or prompt guidance only after replay validation detects no direct regressions, keeping accepted updates auditable, editable, and reusable.

Zelong Zhao, Zhihui Shi, Min-Qi Shi · 0 citations