@Rancho99437786@realNingYu@debfx@liuziwei7@qhnmoon If the query tile is the same size as the frame, the method reduces to standard self-attention. Smaller tiles reduce peak attention memory from O(N^2) to O(BN) where B is the tile size, at the cost of additional tiling overhead and repeated global K/V access. Compute is the same.
For the first time, open-source video diffusion models such as Wan can generate high-fidelity 4K videos without any additional fine-tuning, entirely at inference time!
🚀 Excited to share our recent paper, CineScale! 🎉
🌐 Project Page: https://t.co/3SdAqCv2Vn
@Otnashii@toyxyz3@realNingYu@debfx@liuziwei7@qhnmoon Yes. Although CineScale was not developed specifically for MiniMax H3, it is theoretically applicable to all RoPE-based video models. Since both H3 and Wan2.2 use 3D RoPE over temporal and spatial dimensions, adapting CineScale to H3 should be straightforward!
Wan 2.2 is changing the game for AI Video action control! 🎬🚀
I tested LTX 2.3 vs Wan 2.2 using the "Prompt Relay Timeline" technique.
Result? Wan 2.2 performed a 5-action sequence with incredible precision.
Character consistency stays 💯 while movements shift frame by frame.
Full comparison & Workflow: 👇
🔗 https://t.co/R35mOFsaxV
#Wan22 #LTX23 #ComfyUI #AI视频 #PromptRelay
🎬 VChain is accepted to #ACL2026 Findings! 🚀
#VChain is an inference-time framework that injects reasoning signals (*Chain-of-Visual-Thought*) from MLLMs to guide video generation for better consistency.
🔗 Website: https://t.co/qbm4usAAVb
📄 Paper: https://t.co/vHphF0rP75
I just ran a new zombie chase test using our LTX 2.3 @LTXStudio Prompt Relay @ComfyUI workflow. I purposely made this scene extremely difficult. We added full-body running, multiple zombies, store shelves, scattered objects, and fast camera movements.
Standard video models usually fail right here. They break the environment completely.
But look at our result. Prompt Relay kept the exact action and the entire digital scene perfectly consistent.
I just built a new ComfyUI workflow combining LTX 2.3 and Prompt Relay. It gives us absolute control over our video edits.
You don't have to guess when an action occurs anymore. We can generate a 20-second video, and you decide the exact second every single event happens.
Youtube Video is coming. I'll post the video for you soon.
🤩Excited to see that our *Prompt-Relay* enables fine-grained temporal control in video generation for multi-event storytelling @ChenGordon19
🧑💻*Prompt-Relay* has already been incorporated into Wan and LTX.
- Project: https://t.co/l4C3NdEMRQ
- Code: https://t.co/bAPuzAw0Qt
@cfryant@toyxyz3 Prompt Relay allows you to control exactly what happens at each second of the video :). I’ve linked my Project Page here: https://t.co/bacWSZuJbJ
@toyxyz3 I recommend using additional prompts to form transitions between events. As two prompts that are totally unrelated may cause cuts in between segments. Having these additional prompts will make the video more seamless :)
What a crazy week in AI! 🚀
Opus 4.7
Qwen 3.6
Ternary Bonsai
GPT Rosalind
AniGen
Happy Oyster
Lyra 2
HY World 2.0
Prompt Relay
MotifVideo
OmniShow
Gemini 3.1 TTS
& more!
Watch the full recap:
https://t.co/a1CYNnvDaG
Text-to-video models suck at storytelling. Prompt a sequence of events and the concepts just bleed together into a messy hallucination.
Prompt Relay fixes this. It modifies cross-attention at inference time so each video segment only sees its assigned prompt.
The result is perfect timeline control:
• Zero retraining
• Zero extra compute
• Plug-and-play
Project demo page is available.
#AI #VideoGeneration