3 papers
cs.LG2026
BWTA: Accurate and Efficient Binarized Transformer by Algorithm-Hardware Co-design
Yifu Ding, Xianglong Liu, Shenghao Jin +2
Ultra low-bit quantization brings substantial efficiency for Transformer-based models, but the accuracy degradation and limited GPU support hinder its wide usage. In this paper, we…
cs.LG2026
Diagonal-Tiled Mixed-Precision Attention for Efficient Low-Bit MXFP Inference
Yifu Ding, Xinhao Zhang, Jinyang Guo
Transformer-based large language models (LLMs) have demonstrated remarkable performance across a wide range of real-world tasks, but their inference cost remains prohibitively high…
cs.CV2025
VORTA: Efficient Video Diffusion via Routing Sparse Attention
Wenhao Sun, Rong-Cheng Tu, Yifu Ding +4
Video diffusion transformers have achieved remarkable progress in high-quality video generation, but remain computationally expensive due to the quadratic complexity of attention o…