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|Date|Title|Paper|Code|Recom|
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|2024.08| 🔥[**Transfusion**] Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model(@meta)|[[pdf]](https://www.arxiv.org/pdf/2408.11039)|[[transfusion-pytorch]](https://github.com/lucidrains/transfusion-pytorch)|⭐️⭐️ |
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|2024.08| 🔥[**Transfusion**] Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model(@meta)|[[pdf]](https://www.arxiv.org/pdf/2408.11039)|[[transfusion-pytorch]](https://github.com/A-suozhang/MixDQ)|⭐️⭐️ |
|2024.08| 🔥[**ViDiT-Q**] ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation (@THU&Infinigence AI.)|[[pdf]](https://arxiv.org/abs/2406.02540)|[[viditq]](https://github.com/thu-nics/ViDiT-Q)|⭐️⭐️|
|2024.08| 🔥[**LBQ**] Low-Bitwidth Floating Point Quantization for Efficient High-Quality Diffusion Models(@toronto.edu)|[[pdf]](https://arxiv.org/pdf/2408.06995)|⚠️|⭐️⭐️ |
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|2024.08| 🔥[**EE-Diffusion**] A Simple Early Exiting Framework for Accelerated Sampling in Diffusion Models(@KAIST AI)|[[pdf]](https://arxiv.org/pdf/2408.05927)|[[ee-diffusion]](https://github.com/taehong-moon/ee-diffusion)|⭐️⭐️ |
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