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arXiv Machine Learning By Luran Wang, Linrui Ma, Hannes St\"ark, Regina Barzilay

Specificity-Aware Diffusion Steering via Variance-Reduced Sequential Monte Carlo

Read the original on arXiv Machine Learning →

The paper introduces a method for specificity‑aware diffusion steering that suppresses undesired samples while preserving desired ones. By formulating the problem as a target‑design task, it derives a time‑dependent target distribution based on overlap between positive and negative reference distributions, and samples from it using a variance‑reduced Sequential Monte Carlo (SMC) sampler. Experiments on synthetic, class‑contrastive, text‑to‑image, and peptide‑MHC tasks demonstrate reduced mode shift, improved sampling stability, and better suppression of undesired regions compared to negative‑guidance baselines.

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