2 papers
cs.CL2025
Can the capability of Large Language Models be described by human ability? A Meta Study
Mingrui Zan, Yunquan Zhang, Boyang Zhang +2
Users of Large Language Models (LLMs) often perceive these models as intelligent entities with human-like capabilities. However, the extent to which LLMs' capabilities truly approx…
cs.DC2024
Rubick: Exploiting Job Reconfigurability for Deep Learning Cluster Scheduling
Xinyi Zhang, Hanyu Zhao, Wencong Xiao +5
The era of large deep learning models has given rise to advanced training strategies such as 3D parallelism and the ZeRO series. These strategies enable various (re-)configurable e…