2 papers
cs.AI2026
AscendKernelGen: A Systematic Study of LLM-Based Kernel Generation for Neural Processing Units
Xinzi Cao, Jianyang Zhai, Pengfei Li +17
To meet the ever-increasing demand for computational efficiency, Neural Processing Units (NPUs) have become critical in modern AI infrastructure. However, unlocking their full pote…
q-bio.BM2025
OmniESI: A unified framework for enzyme-substrate interaction prediction with progressive conditional deep learning
Zhiwei Nie, Hongyu Zhang, Hao Jiang +8
Understanding and modeling enzyme-substrate interactions is crucial for catalytic mechanism research, enzyme engineering, and metabolic engineering. Although a large number of pred…