# Training-free VISTA method chooses which denoising steps receive Sequential Monte Carlo guidance under a fixed compute budget

The authors replace fixed sparse-guidance heuristics with a dynamic program that minimizes a bound on deviation from full guidance, and they test it on text, biological sequences and images.

- Published: 2026-10-17T06:12:13.157Z
- Canonical: https://polylog.news/ai/2026-10-17/training-free-vista-method-chooses-which-denoising-steps-rec
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [arXiv cs.AI](https://arxiv.org/abs/2610.20669), [arXiv (HTML)](https://arxiv.org/html/2610.20669)

Reward-guided discrete diffusion lets a model align its outputs with a downstream objective at inference time, without retraining. Sequential Monte Carlo (SMC) guidance is a common way to do this. Each guided step needs extra reward evaluat…

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