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Scaling laws for neural language models
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Universal One-third Time Scaling in Learning Peaked Distributions
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Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients
arXiv:2606. 25008v1 Announce Type: new Abstract: Neural scaling laws describe how pre-training loss decays as power laws with training time, model size, and compute.
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On the Smallness of the Large Language Models Scaling Exponents
arXiv:2606. 24504v1 Announce Type: new Abstract: We discuss reasons why the scaling exponents of current Large Language Models (LLMs) applications are indicating an unsustainable regime in terms of energy resources.
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Neuron Populations Exhibit Divergent Selectivity with Scale
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OpenAI Blog
May 9, 2023
Language models can explain neurons in language models
We use GPT-4 to automatically write explanations for the behavior of neurons in large language models and to score those explanations. We release a dataset of these (imperfect) explanations and scores for every neuron in GPT-2.