Shuncheng Jie, Desen Sun, Ri Hong, Yuyang Tian, Hong Zhang, Sihang Liu · 2026 · arXiv
DOI: 10.48550/arXiv.2610.29733 · open-access PDF
Transformer difusi banyak digunakan dalam layanan pengeditan gambar. Untuk mempertahankan efisiensi dan privasi, sistem yang ada biasanya bergantung pada kolaborasi cloud-device. Menjaga inferensi spesifik permintaan pada perangkat menghindari mengirimkan gambar pribadi dan panggilan ke awan. beban kerja ini sering menggunakan template umum, seperti dalam face swapping dan virtual try-on, memungkinkan KV state untuk dikomputasi dan digunakan kembali di seluruh permintaan. Namun, keadaan yang dapat digunakan kembali ini besar dan berukuran besar dengan jumlah template, membuatnya tidak praktis untuk menyimpannya semua pada perangkat seluler. Menyimpannya di cloud
Machine translation (Meta M2M100); the English original follows.
Diffusion transformers are widely used in image-editing services. To preserve both efficiency and privacy, existing systems commonly rely on cloud-device collaboration. Keeping request-specific inference on the device avoids sending personal images and prompts to the cloud. These workloads often use common templates, such as in face swapping and virtual try-on, enabling KV state to be precomputed and reused across requests. However, this reusable state is large and scales with the number of templates, making it impractical to store all of them on mobile devices. Storing them in the cloud addre
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