Open Access
| Issue |
ITM Web Conf.
Volume 84, 2026
2026 International Conference on Advent Trends in Computational Intelligence and Data Science (ATCIDS 2026)
|
|
|---|---|---|
| Article Number | 03033 | |
| Number of page(s) | 7 | |
| Section | Large Language Models, Generative AI, and Multimodal Learning | |
| DOI | https://doi.org/10.1051/itmconf/20268403033 | |
| Published online | 06 April 2026 | |
- Y. Song, J. Sohl-Dickstein, D. P. Kingma, A. Kumar, S. Ermon, & B. Poole. Score-based generative modeling through stochastic differential equations. In Proceedings of the International Conference on Learning Representations (ICLR), (2021) [Google Scholar]
- C. Lu, Y. Zhou, F. Bao, J. Chen, C. Li, & J. Zhu. DPM-solver: A fast ODE solver for diffusion probabilistic model sampling in around 10 steps. Advances in Neural Information Processing Systems (NeurIPS), 35, 5775–5787, (2022) [Google Scholar]
- Y. Song, P. Dhariwal, M. Chen, & I. Sutskever. Consistency models. In Proceedings of the 40th International Conference on Machine Learning (ICML), 202, 32211–32252, (2023) [Google Scholar]
- Z. Tang, Y. Chen, H. Chen, S. Yan, & K. Ma. Accelerating parallel sampling of diffusion models. In Proceedings of the 41st International Conference on Machine Learning (ICML), (2024) [Google Scholar]
- W. Kong, Y. Zhang, S. Guo, X. Liu, Y. Wang, & D. Chen. Cambricon-D: Full-network differential acceleration for diffusion models. In Proceedings of the 51st International Symposium on Computer Architecture (ISCA), 1–13, (2024) [Google Scholar]
- W. Peebles, & S. Xie. Scalable diffusion models with transformers. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 4195–4205, (2023) [Google Scholar]
- Y. Lipman, R. T. Q. Chen, H. Ben-Hamu, M. Nickel, & M. Le. Flow matching for generative modeling. arXiv preprint arXiv:2210.02747, (2022) [Google Scholar]
- T. Zheng, X. Wang, & Q. Liu. Non-uniform timestep sampling: Towards faster diffusion model training. In Proceedings of the ACM International Conference on Multimedia (ACM MM), 1234–1243, (2024) [Google Scholar]
- A. Sabour, S. Fidler, & K. Kreis. Align your steps: Optimizing sampling schedules in diffusion models. arXiv preprint arXiv:2404.14507, (2024) [Google Scholar]
- A. Sauer, K. Schwarz, & A. Geiger. Fast High-Resolution Image Synthesis with Latent Adversarial Diffusion Distillation. ACM Transactions on Graphics (TOG), 43(6), Article 283, (2024) [Google Scholar]
- Y. Park, S. Kim, J. Lee, & D. Han. RADiT: Redundancy-aware diffusion transformer acceleration. In Proceedings of the Design Automation Conference (DAC), (2025) [Google Scholar]
- X. Hu, J. Chen, Y. Wang, & Q. Liu. ELLA: Equip diffusion models with LLM for enhanced semantic alignment. arXiv preprint arXiv:2403.05135, (2024) [Google Scholar]
- O. Bar-Tal, D. Ofri-Amar, R. Fridman, Y. Kasten, & T. Dekel. Lumiere: A space-time diffusion model for video generation. In SIGGRAPH Asia 2024 Conference Papers (SA ‘ 24), Article 27, (2024) [Google Scholar]
- G. Li, & C. Cai. Breaking AR’s sampling bottleneck: Provable acceleration via diffusion language models. The Thirty-ninth Annual Conference on Neural Information Processing Systems (NeurIPS), (2025) [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

