Semantic Reasoning Denoising: Correcting Language Model Reasoning with Semantic Operators
Large language models can produce fluent reasoning traces whose local semantic errors propagate to an incorrect conclusion, while unconstrained self-correction may preserve, amplify, or introduce errors. Existing diffusion language models provide iterative refinement, but usually define noise as token masking or replacement rather than as errors in the reasoning process. We present Semantic Reasoning Denoising (SRD), an operatorized Markov denoising method for natural-language reasoning trajectories. SRD represents semantic noise with executable error operators that describe the error type, its location, and the corrupted and repaired propositions. Composing these operators constructs pro...
| Authors | Yujiao Yang |
|---|---|
| Primary category | cs.CL |
| Published | 22 August 2026 |
| Last updated at source | 22 August 2026 |
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