3 papers
cs.LG2026
Amortizing Scaling Law Construction Costs
Abhash Kumar Jha, Diana Alexandra Onuţu, Neeratyoy Mallik +6
Scaling laws guide the design choices for training large foundation models, but deriving them involves training an exhaustive grid over hyperparameters, token budgets, and paramete…
cs.LG2026
Deriving Scaling Laws for OpenEuroLLM Models: Learning Rate, Batch Size and Loss
Niccolò Ajroldi, Diana Alexandra Onutu, Haider Al-Tahan +4
We study the scaling behavior of learning rate and batch size in pretraining dense large language models on English-prevalent corpora. Beyond scaling jointly optimal learning rates…
astro-ph.CO2025
Score Matching on Large Geometric Graphs for Cosmology Generation
Diana-Alexandra Onutu, Yue Zhao, Joaquin Vanschoren +1
Generative models are a promising tool to produce cosmological simulations but face significant challenges in scalability, physical consistency, and adherence to domain symmetries,…