Diffusion Timestep Scheduling

Ask about this topic

Momentum

7 papers in the last four weeks, up 133% on the four weeks before. 0.1% of all new papers.

Jul 13Week of Sep 28
View on map

Latest papers 29

All topics
CardsList

  1. Streaming-Aware Diffusion for Real-Time Video Super-Resolution via Cross-Step Attention

    Oct 8, 2026Harris Partaourides, Sotirios ChatzisVideo Super-ResolutionDiffusion Model Inference Acceleration

    Ethical AI Novelties Limassol, Cyprus · Cyprus University of Technology Limassol, Cyprus

  2. Energy-Conditioned Noise Schedule and Whitening for Spectral Diffusion

    Oct 5, 2026Bata Vasic, Bane VasicImage GenerationDiffusion Timestep Scheduling

    University of Nis, Faculty of Electronic Engineering, Aleksandra Medvedeva 4, Nis, 18104,, Serbia

  3. The Golden Path Hypothesis: Reusable Schedules in Diffusion Caching

    Sep 30, 2026Dong Wang, Wenwu Tang, Francesco Corti +3Diffusion Model CachingDiffusion Timestep Scheduling

    Graz University of Technology, Austria · Swiss Data Science Center, Switzerland · ETH Zurich, Switzerland +1

  4. Sol-H3: Recursive Self-Improvement for MiniMax-H3 Inference Acceleration on Sol-Engine across Cloud and Edge

    Sep 28, 2026Yitong Li, Jincheng Yu, Junsong Chen +6Video Diffusion ModelsGPU Kernel Optimization

    NVIDIA Research, Efficient AI Team & Singapore Lab.

  5. GeoShrink: Accelerating Diffusion Transformers with Two Lines of Code

    Sep 27, 2026Haosen Li, Wenshuo Chen, Shaofeng Liang +3Video Diffusion ModelsDiffusion Transformer

    The Hong Kong University of Science and Technology (Guangzhou) · Griffith University · Data61, CSIRO +1

  6. Schedule optimization for tau-leaping in masked discrete diffusion

    Sep 18, 2026Cecilia Secchi, Giacomo ZanellaMasked Diffusion ModelsDiffusion Sampling

    Bocconi University, Department of Decision Sciences, Milan, Italy. · Bocconi University, Department of Decision Sciences and BIDSA, Milan, Italy.

  7. Efficient Text-to-Image Generation: An Adaptive Step Schedule Controller for Diffusion Models

    Sep 15, 2026Kuluhan Binici, Cihan Acar, Shivam Aggarwal +2Diffusion Model SamplingDiffusion Timestep Scheduling

    1SAP · 2National University of Singapore · Institute for Infocomm Research (I2R), A*STAR, Singapore

  8. CrossDistill: Balancing Quality and Diversity via Trajectory-Level Hybrid Few-Step Distillation

    Sep 13, 2026Yuxi Liu, Haoyu Li, Yixiang Cai +8Video Diffusion ModelsDiffusion Model Distillation

    Peking University, Melon Group · Alibaba Group · Tsinghua University

  9. Model-Aware Schedules Improve Generation via Fiberwise Optimal Transport

    Sep 12, 2026Luyi Jia, Boyan Zhang, Yilun Liu +1Flow MatchingDiffusion Timestep Scheduling

    Arnold-Sommerfeld-Center for Theoretical Physics, Ludwig-Maximilians-Universität München, Munich, Germany · Institute of Informatics, Ludwig-Maximilians-Universität München, Munich, Germany · Munich Center for Machine Learning, Munich, Germany

  10. Generative Diffusion Surrogates with Analytical Variance Schedule

    Sep 1, 2026Patrick Reichherzer, Gianluca Gregori, David N. Hosking +1Diffusion Timestep Scheduling

    Department of Physics, University of Oxford, Oxford OX1 3PU, UK. · Department of Astrophysical Sciences, Princeton University, Princeton NJ 08544, USA. · Max Planck Institute for Security and Privacy, Bochum 44799, Germany. +2

  11. Discrete Diffusion Bridges for Spatiotemporally Aligned Image Translation and Generation

    Aug 30, 2026Xing Xie, Jiawei Liu, Shijun Zhou +4Masked Diffusion ModelsImage-to-Image Translation

    State Key Laboratory of Robotics and Intelligent Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China · University of Chinese Academy of Sciences, Beijing, China · School of Computing and Data Science, The University of Hong Kong, Hong Kong

  12. The data geometry of masking diffusion: Certified-optimal schedules via unmasking growth complexity

    Aug 13, 2026Martin J. WainwrightMasked Diffusion ModelsDiffusion Sampling

    Lab for Information and Decision Systems · Statistics and Data Science Center · EECS and Mathematics

  13. Analytic Distribution of Classifier-Free Guidance for Schedule Design

    Jul 22, 2026Enze Jiang, Zheng MaClassifier-Free GuidanceDiffusion Sampling

    School of Mathematical Sciences Shanghai Jiao Tong University Shanghai, China

  14. D2PO: Optimizing Diffusion Samplers via Dynamic Preference

    Jul 7, 2026Jinkyu Kim, Jinyoung Choi, Bohyung HanDiffusion Model AlignmentDirect Preference Optimization

    1ECE & 2IPAI, Seoul National University, Korea · 3AIGS, Ulsan National Institute of Science and Technology, Korea

  15. Adaptive Reparametrized Time for Score-Based Diffusion Sampling

    Jul 2, 2026Yilie Huang, Wenpin Tang, Xun Yu ZhouDiffusion SamplingAdaptive Sampling

    Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong. · Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. · Department of Industrial Engineering and Operations Research and Data Science Institute, Columbia University, New York, NY 10027, USA.

  16. Learning When to Denoise: Optimizing Asynchronous Schedules for Latent Diffusion

    Jun 18, 2026Bingshuo Qian, Xiang ChengFlow MatchingLatent Diffusion Models

    Department of Electrical and Computer Engineering Duke University

  17. Timestep Rescheduling in Diffusion Inversion

    Jun 13, 2026Shangquan Sun, Ting Gong, Zhirui Liu +5Diffusion Model InversionDiffusion Sampling

    School of CyberScience and Technology, Sun Yat-sen University, Shenzhen Campus, Shenzhen 518107, China · Tsinghua University · CUHK +2

  18. Tracing the Oracle: Improving Diffusion Timestep Scheduling for 3D CT Reconstruction

    Jun 4, 2026Yujia Wu, Zhaoqiang LiuDiffusion SamplingFew-Step Diffusion Sampling

    The authors are with the School of Computer Science and Engineering, University of Electronic Science and Technology of China.

  19. DEMON: Diffusion Engine for Musical Orchestrated Noise

    May 27, 2026Ryan FosdickControllable Music GenerationAudio Diffusion Models

    Daydream

  20. Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules

    May 26, 2026Junseo Bang, Dong Ju Mun, Hoigi Seo +2Diffusion Model GuidanceDiffusion Timestep Scheduling

    Dept. of Electrical and Computer Engineering · INMC · IPAI & AIIS

  21. Noise Schedule Design for Diffusion Models: An Optimal Control Perspective

    May 21, 2026Seo Taek Kong, Weina Wang, R. SrikantDiffusion SamplingDiffusion-Based Image Generation

    ECE & CSL University of Illinois Urbana-Champaign · Computer Science Department Carnegie Mellon University · ECE, CSL & NCSA University of Illinois Urbana-Champaign

  22. Semantic Granularity Navigation in Image Editing

    May 20, 2026Liangsi Lu, Minzhe Guo, Xuhang Chen +1Diffusion Model SamplingDiffusion Timestep Scheduling

    Guangdong University of Technology, Guangzhou, China · Huizhou University, Huizhou, China.

  23. Is Monotonic Sampling Necessary in Diffusion Models?

    May 12, 2026Muhammad Haris KhanDiffusion SamplingDiffusion Timestep Scheduling

    Department of Computer Science, University of Copenhagen, Denmark

  24. Steering Without Breaking: Mechanistically Informed Interventions for Discrete Diffusion Language Models

    May 8, 2026Hanhan Zhou, Shamik Roy, Rashmi GangadharaiahLanguage Model SteeringDiffusion Language Model Decoding

    AWS AI Labs Santa Clara, CA 95054

  25. NoiseGate: Learning Per-Latent Timestep Schedules as Information Gating in World Action Models

    May 8, 2026Wen Huang, Haoran Sun, Yongjian Guo +8Action-Conditioned Video GenerationAction-Conditioned World Models

    Tsinghua University · Peking University · JDT AI Infra +1

  26. Information-geometric adaptive sampling for graph diffusion

    Apr 30, 2026Yuhui Lu, Wenjing Liu, Kun ZhanInformation GeometryGraph Generation

    School of Information Science and Engineering, Lanzhou University, Gansu, China.

  27. Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation

    Apr 21, 2026Johannes Schusterbauer, Ming Gui, Yusong Li +3Diffusion Model SamplingDiffusion Sampling

  28. Formalizing the Sampling Design Space of Diffusion-Based Generative Models via Adaptive Solvers and Wasserstein-Bounded Timesteps

    Feb 13, 2026Sangwoo Jo, Sungjoon ChoiDiffusion Model SamplingDiffusion Sampling

    Department of Artificial Intelligence, Korea University, Seoul, South Korea.

  29. ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule

    Jan 26, 2026Yilie Huang, Wenpin Tang, Xunyu ZhouDiffusion SamplingAdaptive Sampling

    Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. · Department of Industrial Engineering and Operations Research & Data Science Institute, Columbia University, New York, NY 10027, USA.