24 citations · 43 across the 5 of their papers we have counts for
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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.CL2022★ 5 cited
Language models are better than humans at next-token prediction
Buck Shlegeris, Fabien Roger, Lawrence Chan +1
Current language models are considered to have sub-human capabilities at natural language tasks like question-answering or writing code. However, language models are not trained to…