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Slowly Annealed Langevin Dynamics: Theory and Applications to Training-Free Guided Generation

Slowly Annealed Langevin Dynamics tracks moving targets via time slowdown with non-asymptotic convergence guarantees, and velocity-aware extension enables training-free guided diffusion generation with convergence theory.

Atsushi Nitanda, Dake Bu, Yueming LYU, Tanya Veeravalli

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 8 of 20 reviewers recommend it
lenient 3/5
medium 4/10
strict 1/5