most citedWhat Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization?

23 citations · 33 across the 4 of their papers we have counts for

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stat.ML2021★ 1 cited

Is the Number of Trainable Parameters All That Actually Matters?

Amélie Chatelain, Amine Djeghri, Daniel Hesslow +2

Recent work has identified simple empirical scaling laws for language models, linking compute budget, dataset size, model size, and autoregressive modeling loss. The validity of th…

stat.ML2021

Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra

Daniel Hesslow, Alessandro Cappelli, Igor Carron +6

Randomized Numerical Linear Algebra (RandNLA) is a powerful class of methods, widely used in High Performance Computing (HPC). RandNLA provides approximate solutions to linear alge…