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Julius Berner

@julberner • 1,353 subscribers

Research scientist @nvidia | postdoc @caltech | PhD @univienna | former research intern @MetaAI and @nvidia | views are my own

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Why choose between autoregressive (fast, streaming) and bidirectional (high-quality) video diffusion when a single model can do both even better? Excited to share Flex-Forcing, accepted as spotlight at #ICML2026! 📍Say hi to Chao Liu at our poster: July 9 | 2:30 - 4:15 PM KST | Hall A #3909 Joint work with Xinyin Ma Weili Nie Arash Vahdat Xinchao Wang
1:00
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Why choose between autoregressive (fast, streaming) and bidirectional (high-quality) video diffusion when a single model can do both even better? Excited to share Flex-Forcing, accepted as spotlight at #ICML2026! 📍Say hi to Chao Liu at our poster: July 9 | 2:30 - 4:15 PM KST | Hall A #3909 Joint work with Xinyin Ma Weili Nie Arash Vahdat Xinchao Wang

Julius Berner

10,443 görüntüleme • 3 ay önce

🚀🎬We introduce TMD (Transition Matching Distillation): 480p videos generated from text prompts in < 3 NFEs! 1️⃣Main backbone for feature extraction and lightweight head for iterative refinement 2️⃣Distilled from Wan2.1 14B T2V combining MeanFlow & DMD2 🔗
0:26
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🚀🎬We introduce TMD (Transition Matching Distillation): 480p videos generated from text prompts in < 3 NFEs! 1️⃣Main backbone for feature extraction and lightweight head for iterative refinement 2️⃣Distilled from Wan2.1 14B T2V combining MeanFlow & DMD2 🔗

Julius Berner

17,026 görüntüleme • 9 ay önce

Struggling with slow inference of diffusion and flow models? Check out the video below—I’ve been using our new FastGen library to achieve 7-28x acceleration for text-2-image and {text,image,video}-2-video generation without sacrificing visual fidelity!
2:20
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Struggling with slow inference of diffusion and flow models? Check out the video below—I’ve been using our new FastGen library to achieve 7-28x acceleration for text-2-image and {text,image,video}-2-video generation without sacrificing visual fidelity!

Julius Berner

13,780 görüntüleme • 8 ay önce

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