Stanford-led paper traces 'bigger is better' to data-induced competition for neurons
niloofar_mire · x · 2026-10-24
Chris Potts shares an overview thread of the team's new paper (Huang et al. 2026), led by Jing Huang and Ekdeep Singh Lubana, tackling a taken-for-granted question: why are larger models better than smaller ones?
- The paper traces the advantage to a data-induced competition for resources (neurons)
- The argument combines formal analysis, idealized tasks, and real pretraining runs
- An older thread from the team gives a full overview of the paper
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