1 citations · 1 across the 9 of their papers we have counts for
7 papers · 1 filter
DiffBench Meets DiffAgent: End-to-End LLM-Driven Diffusion Acceleration Code Generation
Jiajun jiao, Haowei Zhu, Puyuan Yang +8
Diffusion models have achieved remarkable success in image and video generation. However, their inherently multiple step inference process imposes substantial computational overhea…
SpecVLM: Fast Speculative Decoding in Vision-Language Models
Haiduo Huang, Fuwei Yang, Zhenhua Liu +4
Speculative decoding is a powerful way to accelerate autoregressive large language models (LLMs), but directly porting it to vision-language models (VLMs) faces unique systems cons…
DL-QAT: Weight-Decomposed Low-Rank Quantization-Aware Training for Large Language Models
Wenjin Ke, Zhe Li, Dong Li +2
Improving the efficiency of inference in Large Language Models (LLMs) is a critical area of research. Post-training Quantization (PTQ) is a popular technique, but it often faces ch…
MonoGS++: Fast and Accurate Monocular RGB Gaussian SLAM
Renwu Li, Wenjing Ke, Dong Li +2
We present MonoGS++, a novel fast and accurate Simultaneous Localization and Mapping (SLAM) method that leverages 3D Gaussian representations and operates solely on RGB inputs. Whi…
Partial Convolution Meets Visual Attention
Haiduo Huang, Fuwei Yang, Dong Li +5
Designing an efficient and effective neural network has remained a prominent topic in computer vision research. Depthwise onvolution (DWConv) is widely used in efficient CNNs or Vi…
EGSRAL: An Enhanced 3D Gaussian Splatting based Renderer with Automated Labeling for Large-Scale Driving Scene
Yixiong Huo, Guangfeng Jiang, Hongyang Wei +9
3D Gaussian Splatting (3D GS) has gained popularity due to its faster rendering speed and high-quality novel view synthesis. Some researchers have explored using 3D GS for reconstr…