Author

Sergey Kastryulin

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Preprint Oct 2026

When Text-to-Image Helps Editing: The Effects of Conditioning During Denoising

Unified models are trained for both instruction-based image editing and text-to-image (T2I) generation, but standard editing pipelines keep source-image conditioning throughout denoising. We ask whether editing can benefit from T2I, and study how the effects of conditioning vary across edits and denoising stages. In pu...

Lidia Troeshestova, A. Ustyuzhanin, Sergey Kastryulin · 0 citations

Preprint Aug 2026

Revisiting Classifier-Free Guidance Methods in Latent Diffusion Models

This study studies a family of training-free techniques conceptually rooted in Classifier-Free Guidance, most of which were originally proposed on older U-Net diffusion models and validated using metrics that assess image quality in isolation, without accounting for compositional alignment or semantic correspondence.

A. Sergievskii, Artyom Turevich, Sergey Kastryulin · 0 citations