> For the complete documentation index, see [llms.txt](https://paper.lingyunyang.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://paper.lingyunyang.com/reading-notes/conference/icml-2025.md).

# ICML 2025

## Meta Info

Homepage: <https://icml.cc/Conferences/2025>

### Acceptance Rate

* 26.9% (= 3260 / 12107)
* Poster: 24.3% (= 2947 / 12107)
* Spotlight: 2.6% (= 313 / 12107)

## Papers

### Diffusion Models

* Video Generation
  * Fast Video Generation with Sliding Tile Attention \[[Paper](https://proceedings.mlr.press/v267/zhang25m.html)] \[[OpenReview](https://openreview.net/forum?id=U74MOXPEJd)] \[[arXiv](https://arxiv.org/abs/2502.04507)] \[[Code](https://github.com/hao-ai-lab/FastVideo)]
    * UCSD & UMich & THU & UC Berkeley & MBZUAI
    * Introduce **STA**, a tile-wise local spatiotemporal attention mechanism for video DiTs that removes redundant full attention.
    * Use a hardware-aware sliding-window design and kernel optimizations to speed up video diffusion attention and end-to-end HunyuanVideo generation.