DDiT: Dynamic Patch Scheduling for Efficient Diffusion Transformers | ScienceToStartup | ScienceToStartup

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References (100)

[1]

Accelerating Vision Transformers with Adaptive Patch Sizes

2025Rohan Choudhury, JungEun Kim et al.

[2]

Seedream 4.0: Toward Next-generation Multimodal Image Generation

2025Yunpeng Chen, Yu Gao et al.

[3]

ToMA: Token Merge with Attention for Diffusion Models

Founder's Pitch

"Develop a dynamic tokenization strategy for Diffusion Transformers to significantly improve computational efficiency in image and video generation."

Diffusion Models•Score: 6•View PDF ↗

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0-10 scale

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2.5

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7.5

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3/4 signals

7.5

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DDiT: Dynamic Patch Scheduling for Efficient Diffusion Transformers

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References (100)

Founder's Pitch

"Develop a dynamic tokenization strategy for Diffusion Transformers to significantly improve computational efficiency in image and video generation."

Commercial Viability Breakdown

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DDiT: Dynamic Patch Scheduling for Efficient Diffusion Transformers

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References (100)

Founder's Pitch

"Develop a dynamic tokenization strategy for Diffusion Transformers to significantly improve computational efficiency in image and video generation."

Commercial Viability Breakdown

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