The proposed Diffusion Transformer (DDT) improves generation quality and inference speed by decoupling semantic encoding and high-frequency decoding, achieving state-of-the-art performance on ImageNet with faster training convergence.https://arxiv.org/abs//2504.05741YouTube: https://www.youtube.com/@ArxivPapersTikTok: https://www.tiktok.com/@arxiv_papersApple Podcasts: https://podcasts.apple.com/us/podcast/arxiv-papers/id1692476016Spotify: https://podcasters.spotify.com/pod/show/arxiv-papers