1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.LG2025
Scaling Laws for Robust Comparison of Open Foundation Language-Vision Models and Datasets
Marianna Nezhurina, Tomer Porian, Giovanni Pucceti +4
In studies of transferable learning, scaling laws are obtained for various important foundation models to predict their properties and performance at larger scales. We show here ho…
cs.LG2024★ 1 cited
Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Tomer Porian, Mitchell Wortsman, Jenia Jitsev +2
Kaplan et al. and Hoffmann et al. developed influential scaling laws for the optimal model size as a function of the compute budget, but these laws yield substantially different pr…