{"total":38,"rows":[{"id":"2503.09583","title":"Minimax Optimality of the Probability Flow ODE for Diffusion Models","created":"2025-03-12","cited_by_count":23,"area":"diffusion"},{"id":"2504.05300","title":"Dimension-Free Convergence of Diffusion Models for Approximate Gaussian Mixtures","created":"2025-04-07","cited_by_count":23,"area":"diffusion"},{"id":"2602.15008","title":"Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees","created":"2026-02-16","cited_by_count":19,"area":"diffusion"},{"id":"2502.05743","title":"Understanding Representation Dynamics of Diffusion Models via Low-Dimensional Modeling","created":"2025-02-09","cited_by_count":18,"area":"diffusion"},{"id":"2603.22248","title":"Confidence-Based Decoding is Provably Efficient for Diffusion Language Models","created":"2026-03-23","cited_by_count":18,"area":"diffusion"},{"id":"2502.04849","title":"Advancing Wasserstein Convergence Analysis of Score-Based Models: Insights from Discretization and Second-Order Acceleration","created":"2025-02-07","cited_by_count":17,"area":"diffusion"},{"id":"2506.24042","title":"Faster Diffusion Models via Higher-Order Approximation","created":"2025-06-30","cited_by_count":16,"area":"diffusion"},{"id":"2510.27562","title":"Optimal Convergence Analysis of DDPM for General Distributions","created":"2025-10-31","cited_by_count":16,"area":"diffusion"},{"id":"2602.01338","title":"High-accuracy sampling for diffusion models and log-concave distributions","created":"2026-02-01","cited_by_count":16,"area":"diffusion"},{"id":"2505.03432","title":"Wasserstein Convergence of Score-based Generative Models under Semiconvexity and Discontinuous Gradients","created":"2025-05-06","cited_by_count":15,"area":"diffusion"},{"id":"2512.20963","title":"Generalization of Diffusion Models Arises with a Balanced Representation Space","created":"2025-12-24","cited_by_count":11,"area":"diffusion"},{"id":"2602.20126","title":"Adaptation to Intrinsic Dependence in Diffusion Language Models","created":"2026-02-23","cited_by_count":10,"area":"diffusion"},{"id":"2506.13061","title":"Fast Convergence for High-Order ODE Solvers in Diffusion Probabilistic Models","created":"2025-06-16","cited_by_count":9,"area":"diffusion"},{"id":"2501.18863","title":"Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models","created":"2025-01-31","cited_by_count":8,"area":"diffusion"},{"id":"2512.04985","title":"Towards a unified framework for guided diffusion models","created":"2025-12-04","cited_by_count":8,"area":"diffusion"},{"id":"2511.04844","title":"Sublinear iterations can suffice even for DDPMs","created":"2025-11-06","cited_by_count":7,"area":"diffusion"},{"id":"2601.10708","title":"High-accuracy and dimension-free sampling with diffusions","created":"2026-01-15","cited_by_count":7,"area":"diffusion"},{"id":"2607.19333","title":"Provable diffusion-based posterior sampling for linear inverse problems via DDIM","created":"2026-07-21","cited_by_count":4,"area":"diffusion"},{"id":"2608.23554","title":"Provably adaptive sampling with uniform and remasking discrete diffusion models","created":"2026-08-24","cited_by_count":4,"area":"diffusion"},{"id":"2512.01820","title":"Dimension-free error estimate for diffusion model and optimal scheduling","created":"2025-12-01","cited_by_count":3,"area":"diffusion"},{"id":"2601.02499","title":"Polynomial Convergence of Riemannian Diffusion Models","created":"2026-01-05","cited_by_count":3,"area":"diffusion"},{"id":"2601.15500","title":"Low-Dimensional Adaptation of Rectified Flow: A Diffusion and Stochastic Localization Perspective","created":"2026-01-21","cited_by_count":3,"area":"diffusion"},{"id":"2603.11319","title":"On the Robustness of Langevin Dynamics to Score Function Error","created":"2026-03-11","cited_by_count":3,"area":"diffusion"},{"id":"2605.30153","title":"Diffusion Models Are Statistically Optimal for Learning Low-Dimensional Multi-Modal Distributions","created":"2026-05-28","cited_by_count":3,"area":"diffusion"},{"id":"2505.18344","title":"Improved Sample Complexity For Diffusion Model Training Without Empirical Risk Minimizer Access","created":"2025-05-23","cited_by_count":2,"area":"diffusion"},{"id":"2505.20123","title":"Understanding Generalization in Diffusion Distillation via Probability Flow Distance","created":"2025-05-26","cited_by_count":2,"area":"diffusion"},{"id":"2605.18069","title":"Wasserstein bounds for denoising diffusion probabilistic models via the F\\\"ollmer process","created":"2026-05-18","cited_by_count":2,"area":"diffusion"},{"id":"2508.10944","title":"Non-asymptotic convergence bound of conditional diffusion models","created":"2025-08-13","cited_by_count":1,"area":"diffusion"},{"id":"2601.21943","title":"Entropy-Based Dimension-Free Convergence and Loss-Adaptive Schedules for Diffusion Models","created":"2026-01-29","cited_by_count":1,"area":"diffusion"},{"id":"2603.19670","title":"Load--Reserve Wasserstein Propagation for Isotropic Diffusion Samplers","created":"2026-03-20","cited_by_count":1,"area":"diffusion"},{"id":"2605.07220","title":"On the Robustness of Distribution Support under Diffusion Guidance","created":"2026-05-08","cited_by_count":1,"area":"diffusion"},{"id":"2605.13448","title":"On the Limits of Latent Reuse in Diffusion Models","created":"2026-05-13","cited_by_count":1,"area":"diffusion"},{"id":"2606.06007","title":"Diffusion Models for Adaptive Sequential Data Generation","created":"2026-06-04","cited_by_count":1,"area":"diffusion"},{"id":"2606.23627","title":"Diffusion Models Adapt to Low-Dimensional Structure Under Flexible Coefficient Choices","created":"2026-06-22","cited_by_count":1,"area":"diffusion"},{"id":"2604.10074","title":"Transformers Learn the Optimal DDPM Denoiser for Multi-Token GMMs","created":"2026-04-11","cited_by_count":0,"area":"diffusion"},{"id":"2605.07969","title":"When Diffusion Model Can Ignore Dimension: An Entropy-Based Theory","created":"2026-05-08","cited_by_count":0,"area":"diffusion"},{"id":"2610.10190","title":"Universal Local Error and Realized Amplification for the First-Order EDM Predictor","created":"2026-10-07","cited_by_count":0,"area":"diffusion"},{"id":"2610.10640","title":"How Many Directions Must a Truncated Diffusion Sampler Retain? Matching Bounds Under Power-Law Spectra","created":"2026-10-07","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}