{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T16:37:26Z","timestamp":1776357446669,"version":"3.51.2"},"publisher-location":"New York, NY, USA","reference-count":37,"publisher":"ACM","funder":[{"name":"National Natural Science Foundation of China (NSFC)","award":["62272050"],"award-info":[{"award-number":["62272050"]}]},{"name":"National Natural Science Foundation of China (NSFC)","award":["62302048"],"award-info":[{"award-number":["62302048"]}]},{"name":"Zhuhai Science-Tech Innovation Bureau","award":["2320004002772"],"award-info":[{"award-number":["2320004002772"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,4]]},"DOI":"10.1145\/3798065.3798079","type":"proceedings-article","created":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T19:30:21Z","timestamp":1775676621000},"page":"92-98","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Accelerating Diffusion Model Inference via Semantics-Aware Trajectory Reuse and Adaptive Scheduling"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5988-5470","authenticated-orcid":false,"given":"Hanshuai","family":"Cui","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Beijing Normal University, Beijing, China and Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhai, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9375-4818","authenticated-orcid":false,"given":"Zhiqing","family":"Tang","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhai, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4421-3804","authenticated-orcid":false,"given":"Zhi","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Beijing Normal University, Beijing, China and Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhaizhu, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1000-3937","authenticated-orcid":false,"given":"Weijia","family":"Jia","sequence":"additional","affiliation":[{"name":"Institute of Artificial Intelligence and Future Networks, Beijing Normal University, Zhuhai, Guangdong, China and Beijing Normal-Hong Kong Baptist University, Zhuhai, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2026,4,8]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"Improved algorithms for linear stochastic bandits. NeurIPS 24","author":"Abbasi-Yadkori Yasin","year":"2011","unstructured":"Yasin Abbasi-Yadkori, D\u00e1vid P\u00e1l, and Csaba Szepesv\u00e1ri. 2011. Improved algorithms for linear stochastic bandits. NeurIPS 24 (2011)."},{"key":"e_1_3_2_1_2_1","unstructured":"Shubham Agarwal Subrata Mitra Sarthak Chakraborty et al. 2024. Approximate caching for efficiently serving Text-to-Image diffusion models. In NSDI. 1173\u20131189."},{"key":"e_1_3_2_1_3_1","doi-asserted-by":"crossref","unstructured":"Emanuele Artioli Farzad Tashtarian and Christian Timmerer. 2025. End-to-End Learning-based Video Streaming Enhancement Pipeline: A Generative AI Approach. In NOSSDAV. 50\u201356.","DOI":"10.1145\/3712678.3721881"},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1023\/A:1013689704352"},{"key":"e_1_3_2_1_5_1","volume-title":"Gptcache: An open-source semantic cache for llm applications enabling faster answers and cost savings. In NLP-OSS. 212\u2013218.","author":"Bang Fu","year":"2023","unstructured":"Fu Bang. 2023. Gptcache: An open-source semantic cache for llm applications enabling faster answers and cost savings. In NLP-OSS. 212\u2013218."},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3704262"},{"key":"e_1_3_2_1_7_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. In NAACL. 4171\u20134186.","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. Bert: Pre-training of deep bidirectional transformers for language understanding. In NAACL. 4171\u20134186."},{"key":"e_1_3_2_1_8_1","first-page":"8780","article-title":"Diffusion models beat gans on image synthesis","volume":"34","author":"Dhariwal Prafulla","year":"2021","unstructured":"Prafulla Dhariwal and Alexander Nichol. 2021. Diffusion models beat gans on image synthesis. In NeurIPS, Vol. 34. 8780\u20138794.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2024.3356178"},{"key":"e_1_3_2_1_10_1","unstructured":"Patrick Esser Sumith Kulal Andreas Blattmann Rahim Entezari Jonas M\u00fcller Harry Saini Yam Levi Dominik Lorenz Axel Sauer Frederic Boesel et al. 2024. Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. arXiv preprint arXiv:2403.03206 (2024)."},{"key":"e_1_3_2_1_11_1","volume-title":"ICML. Pmlr","author":"Haarnoja Tuomas","year":"2018","unstructured":"Tuomas Haarnoja, Aurick Zhou, Pieter Abbeel, and Sergey Levine. 2018. Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor. In ICML. Pmlr, 1861\u20131870."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"crossref","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep residual learning for image recognition. In CVPR. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"e_1_3_2_1_13_1","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume":"33","author":"Ho Jonathan","year":"2020","unstructured":"Jonathan Ho, Ajay Jain, and Pieter Abbeel. 2020. Denoising diffusion probabilistic models. In NeurIPS, Vol. 33. 6840\u20136851.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_14_1","doi-asserted-by":"crossref","unstructured":"ZQ John Lu. 2010. The elements of statistical learning: data mining inference and prediction.","DOI":"10.1111\/j.1467-985X.2010.00646_6.x"},{"key":"e_1_3_2_1_15_1","first-page":"36652","article-title":"Pick-a-pic: An open dataset of user preferences for text-to-image generation","volume":"36","author":"Kirstain Yuval","year":"2023","unstructured":"Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, and Omer Levy. 2023. Pick-a-pic: An open dataset of user preferences for text-to-image generation. In NeurIPS, Vol. 36. 36652\u201336663.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_16_1","doi-asserted-by":"crossref","unstructured":"Lihong Li Wei Chu John Langford and Robert E Schapire. 2010. A contextual-bandit approach to personalized news article recommendation. In WWW. 661\u2013670.","DOI":"10.1145\/1772690.1772758"},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Tsung-Yi Lin Michael Maire Serge Belongie James Hays Pietro Perona Deva Ramanan Piotr Doll\u00e1r and C Lawrence Zitnick. 2014. Microsoft coco: Common objects in context. In ECCV. 740\u2013755.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"e_1_3_2_1_18_1","first-page":"5775","article-title":"Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps","volume":"35","author":"Lu Cheng","year":"2022","unstructured":"Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu. 2022. Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps. NeurIPS 35 (2022), 5775\u20135787.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_19_1","volume-title":"Deepcache: Accelerating diffusion models for free. In CVPR. 15762\u201315772.","author":"Ma Xinyin","year":"2024","unstructured":"Xinyin Ma, Gongfan Fang, and Xinchao Wang. 2024. Deepcache: Accelerating diffusion models for free. In CVPR. 15762\u201315772."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2889473"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"crossref","unstructured":"David McAllister Matthew Tancik Jiaming Song and Angjoo Kanazawa. 2025. Decentralized diffusion models. In CVPR. 23323\u201323333.","DOI":"10.1109\/CVPR52734.2025.02172"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"crossref","unstructured":"Chenlin Meng Robin Rombach Ruiqi Gao Diederik Kingma Stefano Ermon Jonathan Ho and Tim Salimans. 2023. On distillation of guided diffusion models. In CVPR. 14297\u201314306.","DOI":"10.1109\/CVPR52729.2023.01374"},{"key":"e_1_3_2_1_23_1","unstructured":"Pinecone. 2025. Retrieved March 1 2025 from https:\/\/www.pinecone.io\/learn\/faster- stable- diffusion\/"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2025.3613700"},{"key":"e_1_3_2_1_25_1","volume-title":"Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, et al.","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, et al. 2021. Learning transferable visual models from natural language supervision. In ICML. 8748\u20138763."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"crossref","unstructured":"Robin Rombach Andreas Blattmann Dominik Lorenz Patrick Esser and Bj\u00f6rn Ommer. 2022. High-resolution image synthesis with latent diffusion models. In CVPR. 10684\u201310695.","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"e_1_3_2_1_27_1","volume-title":"Progressive distillation for fast sampling of diffusion models. arXiv preprint arXiv:2202.00512","author":"Salimans Tim","year":"2022","unstructured":"Tim Salimans and Jonathan Ho. 2022. Progressive distillation for fast sampling of diffusion models. arXiv preprint arXiv:2202.00512 (2022)."},{"key":"e_1_3_2_1_28_1","first-page":"36046","article-title":"Multistep distillation of diffusion models via moment matching","volume":"37","author":"Salimans Tim","year":"2024","unstructured":"Tim Salimans, Thomas Mensink, Jonathan Heek, and Emiel Hooge-boom. 2024. Multistep distillation of diffusion models via moment matching. In NeurIPS, Vol. 37. 36046\u201336070.","journal-title":"NeurIPS"},{"key":"e_1_3_2_1_29_1","volume-title":"NeurIPS","volume":"35","author":"Schuhmann Christoph","year":"2022","unstructured":"Christoph Schuhmann, Romain Beaumont, et al. 2022. LAION-5B: An open large-scale dataset for training next generation image-text models. In NeurIPS, Vol. 35. Curran Associates, Inc., 25278\u201325294."},{"key":"e_1_3_2_1_30_1","volume-title":"Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347","author":"Schulman John","year":"2017","unstructured":"John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017. Proximal policy optimization algorithms. arXiv preprint arXiv:1707.06347 (2017)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/125223.125262"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/16856.16888"},{"key":"e_1_3_2_1_33_1","volume-title":"FlexCache: Flexible approximate cache system for video diffusion. arXiv preprint arXiv:2501.04012","author":"Sun Desen","year":"2024","unstructured":"Desen Sun, Henry Tian, Tim Lu, and Sihang Liu. 2024. FlexCache: Flexible approximate cache system for video diffusion. arXiv preprint arXiv:2501.04012 (2024)."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"crossref","unstructured":"Zhongze Tang Zichen Zhu Mengmei Ye Yao Liu and Sheng Wei. 2025. Privacy-Preserving Multimedia Mobile Cloud Computing Using Cost-Effective Protective Perturbation. In NOSSDAV. 36\u201342.","DOI":"10.1145\/3712678.3721879"},{"key":"e_1_3_2_1_35_1","volume-title":"DiffusionDB: A Large-Scale Prompt Gallery Dataset for Text-to-Image Generative Models. arXiv:2210.14896","author":"Wang Zijie J.","year":"2022","unstructured":"Zijie J. Wang, Evan Montoya, David Munechika, Haoyang Yang, Benjamin Hoover, and Duen Horng Chau. 2022. DiffusionDB: A Large-Scale Prompt Gallery Dataset for Text-to-Image Generative Models. arXiv:2210.14896 (2022). https:\/\/arxiv.org\/abs\/2210.14896"},{"key":"e_1_3_2_1_36_1","volume-title":"Dkdm: Data-free knowledge distillation for diffusion models with any architecture. In CVPR. 2955\u20132965.","author":"Xiang Qianlong","year":"2025","unstructured":"Qianlong Xiang, Miao Zhang, Yuzhang Shang, Jianlong Wu, Yan Yan, and Liqiang Nie. 2025. Dkdm: Data-free knowledge distillation for diffusion models with any architecture. In CVPR. 2955\u20132965."},{"key":"e_1_3_2_1_37_1","volume-title":"William Yang Wang, and Lei Li","author":"Zhang Kexun","year":"2023","unstructured":"Kexun Zhang, Xianjun Yang, William Yang Wang, and Lei Li. 2023. ReDi: efficient learning-free diffusion inference via trajectory retrieval. In ICML. 41770\u201341785."}],"event":{"name":"NOSSDAV '26: ACM Multimedia Systems Conference 2026","location":"Hong Kong Hong Kong","acronym":"NOSSDAV '26","sponsor":["SIGMM ACM Special Interest Group on Multimedia"]},"container-title":["Proceedings of the 36th Workshop on Network and Operating System Support for Digital Audio and Video"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3798065.3798079","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T15:33:14Z","timestamp":1776353594000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3798065.3798079"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,4]]},"references-count":37,"alternative-id":["10.1145\/3798065.3798079","10.1145\/3798065"],"URL":"https:\/\/doi.org\/10.1145\/3798065.3798079","relation":{},"subject":[],"published":{"date-parts":[[2026,4,4]]},"assertion":[{"value":"2026-04-08","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}