10 citations · 29 across the 15 of their papers we have counts for
6 papers · 1 filter
HarmoniCa: Harmonizing Training and Inference for Better Feature Caching in Diffusion Transformer Acceleration
Yushi Huang, Zining Wang, Ruihao Gong +5
Diffusion Transformers (DiTs) excel in generative tasks but face practical deployment challenges due to high inference costs. Feature caching, which stores and retrieves redundant…
Temporal Feature Matters: A Framework for Diffusion Model Quantization
Yushi Huang, Ruihao Gong, Xianglong Liu +4
The Diffusion models, widely used for image generation, face significant challenges related to their broad applicability due to prolonged inference times and high memory demands. E…
Selective Focus: Investigating Semantics Sensitivity in Post-training Quantization for Lane Detection
Yunqian Fan, Xiuying Wei, Ruihao Gong +4
Lane detection (LD) plays a crucial role in enhancing the L2+ capabilities of autonomous driving, capturing widespread attention. The Post-Processing Quantization (PTQ) could facil…
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes
Ruihao Gong, Yang Yong, Zining Wang +4
Neural network sparsity has attracted many research interests due to its similarity to biological schemes and high energy efficiency. However, existing methods depend on long-time…
LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit
Ruihao Gong, Yang Yong, Shiqiao Gu +5
Recent advancements in large language models (LLMs) are propelling us toward artificial general intelligence with their remarkable emergent abilities and reasoning capabilities. Ho…
2023 Low-Power Computer Vision Challenge (LPCVC) Summary
Leo Chen, Benjamin Boardley, Ping Hu +27
This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of compu…