3 papers
cs.LG2026
FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models
Bowen Xue, Zihan Min, Xingyang Li +8
Diffusion models have become a dominant paradigm for high-quality generative modeling, while post-training is essential for adapting them to diverse downstream applications. Howeve…
cs.AR2025
Nebula: Enable City-Scale 3D Gaussian Splatting in Virtual Reality via Collaborative Rendering and Accelerated Stereo Rasterization
He Zhu, Zheng Liu, Xingyang Li +6
3D Gaussian splatting (3DGS) has drawn significant attention in the architectural community recently. However, current architectural designs often overlook the 3DGS scalability, ma…
cs.AR2025
SLTarch: Towards Scalable Point-Based Neural Rendering by Taming Workload Imbalance and Memory Irregularity
Xingyang Li, Jie Jiang, Yu Feng +5
Rendering is critical in fields like 3D modeling, AR/VR, and autonomous driving, where high-quality, real-time output is essential. Point-based neural rendering (PBNR) offers a pho…