CRN v2: Lightweight Error Correction for Frozen Language Models

CRN v2 uses a 34M-parameter logit-level module to correct 53.3% of errors in a frozen 4.65B Gemma model. The module is trained via SFT and reference-free DPO without degrading the base model's MMLU or BoolQ capabilities.