Denoising Iterative Self-Correction: Structured Verification Loops for Reliable LLM Reasoning
Large language models produce fluent but often incorrect multi-step reasoning, and naive correction methods risk degrading already-correct answers. We introduce Denoising Iterative Self-Correction (DISC), a test-time procedure that treats verification question outputs as noisy measurements of where a solution may be corrupted. Using these signals, DISC progressively reduces errors across multiple verify-judge-correct passes, analogous to traditional iterative denoising. A binary judgment gate controls correction precision by blocking rewrites that would damage already-correct answers while the verifier and corrector together repair errors. We evaluate this trade-off using two paired diagn...
| Authors | Shen Yin, David Ken, Joel Stremmel |
|---|---|
| Primary category | cs.CL |
| Published | 19 June 2026 |
| Last updated at source | 19 June 2026 |
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