11 citations · 43 across the 16 of their papers we have counts for
3 papers · 1 filter
Self-Data Distillation for Recovering Quality in Pruned Large Language Models
Vithursan Thangarasa, Ganesh Venkatesh, Mike Lasby +2
Large language models have driven significant progress in natural language processing, but their deployment requires substantial compute and memory resources. As models scale, comp…
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed +97
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safe…
MediSwift: Efficient Sparse Pre-trained Biomedical Language Models
Vithursan Thangarasa, Mahmoud Salem, Shreyas Saxena +3
Large language models (LLMs) are typically trained on general source data for various domains, but a recent surge in domain-specific LLMs has shown their potential to outperform ge…