6 citations · 9 across the 8 of their papers we have counts for
3 papers · 1 filter
Liger Kernel: Efficient Triton Kernels for LLM Training
Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli +7
Training Large Language Models (LLMs) efficiently at scale presents a formidable challenge, driven by their ever-increasing computational demands and the need for enhanced performa…
Enhancing Stability for Large Language Models Training in Constrained Bandwidth Networks
Yun Dai, Tejas Dharamsi, Byron Hsu +2
Training extremely large language models (LLMs) with billions of parameters is a computationally intensive task that pushes the limits of current data parallel training systems. Wh…
LiRank: Industrial Large Scale Ranking Models at LinkedIn
Fedor Borisyuk, Mingzhou Zhou, Qingquan Song +31
We present LiRank, a large-scale ranking framework at LinkedIn that brings to production state-of-the-art modeling architectures and optimization methods. We unveil several modelin…