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Stochastic Thermodynamics and SDE-based Generative Models

arXiv 2606.18290 ↗First posted 13 Jun 2026cond-mat.stat-mech cs.LG eess.SPcited by 0

On the map: Diffusion models → Diffusion foundations and sampling

Abstract (arXiv)

SDE-based generative models, including diffusion models and the Schr"odinger bridge, have found broad applications in signal processing tasks such as speech enhancement, image restoration, and time-series generation. This note presents a modeling framework for such models within the context of stochastic thermodynamics. The main results of this note are trajectory-level definitions of work, heat, and entropy production, along with a generalized Jarzynski identity and a second-law-like inequality. The proposed framework extends the original Jarzynski setup to accommodate time-dependent bath temperature and nonconservative driving forces. This thermodynamic perspective may deepen our understanding of diffusion models and the Schr"odinger bridge from a nonequilibrium statistical mechanics viewpoint.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Diffusion foundations and sampling, one of 14 directions in Diffusion models. Builds on 0 of its 1 references that are in the map. First posted on arXiv 13 Jun 2026.

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