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Zhihao Shu

3 accepted papers

2025

LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers

AAAI 2025technical

Diffusion Transformers have emerged as the preeminent models for a wide array of generative tasks, demonstrating superior performance and efficacy across various applications. The promising results come at the cost of slow inference, as each denoising step requires running the whole transformer mode…

2024

Data Overfitting for On-Device Super-Resolution with Dynamic Algorithm and Compiler Co-Design

ECCV 2024poster

"Deep neural networks (DNNs) are frequently employed in a variety of computer vision applications. Nowadays, an emerging trend in the current video distribution system is to take advantage of DNN’s overfitting properties to perform video resolution upscaling. By splitting videos into chunks and appl…

2024

Real-time Core-Periphery Guided ViT with Smart Data Layout Selection on Mobile Devices

NeurIPS 2024poster

Mobile devices have become essential enablers for AI applications, particularly in scenarios that require real-time performance. Vision Transformer (ViT) has become a fundamental cornerstone in this regard due to its high accuracy. Recent efforts have been dedicated to developing various transformer…

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