19 citations · 78 across the 27 of their papers we have counts for
3 papers · 1 filter
Distributed Inference and Fine-tuning of Large Language Models Over The Internet
Alexander Borzunov, Max Ryabinin, Artem Chumachenko +5
Large language models (LLMs) are useful in many NLP tasks and become more capable with size, with the best open-source models having over 50 billion parameters. However, using thes…
One-Step Diffusion Distillation via Deep Equilibrium Models
Zhengyang Geng, Ashwini Pokle, J. Zico Kolter
Diffusion models excel at producing high-quality samples but naively require hundreds of iterations, prompting multiple attempts to distill the generation process into a faster net…
Efficient Online Data Mixing For Language Model Pre-Training
Alon Albalak, Liangming Pan, Colin Raffel +1
The data used to pretrain large language models has a decisive impact on a model's downstream performance, which has led to a large body of work on data selection methods that aim…