I think there's a whole plethora of research on efficient attention implementations (similar to how DeepSeek & Kimi has made strides with theirs in LLMs) [1], [2]. And various techniques to reduce the flow-matching / diffusion iterations ("reflow") [3].
replyCVPR 2026 paper list (after filtering on video generation) might be a good start - asking LLMs to take a look and filter relevant papers sound even better.
[1] https://arxiv.org/abs/2609.15810 [2] https://arxiv.org/abs/2602.13515 [3] https://arxiv.org/abs/2605.23381
Thanks! And sorry, I was just curious to get some opinions on it from people who have worked with that kind of stuff. I feel like someone who has worked on it in a serious capacity will be a better filter than LLM (I don't know enough to provide the right keywords that would give me high signal papers). However, I realized I should probably just read a survey to get some overview on the state if I can't get any answers.
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