24 citations · 24 across the 2 of their papers we have counts for
2 papers
cs.CL2023★ 24 cited
Inverse Scaling: When Bigger Isn't Better
Ian R. McKenzie, Alexander Lyzhov, Michael Pieler +24
Work on scaling laws has found that large language models (LMs) show predictable improvements to overall loss with increased scale (model size, training data, and compute). Here, w…
cs.CL2021
Teaching Autoregressive Language Models Complex Tasks By Demonstration
Gabriel Recchia
This paper demonstrates that by fine-tuning an autoregressive language model (GPT-Neo) on appropriately structured step-by-step demonstrations, it is possible to teach it to execut…