most citedNext-token prediction capacity: general upper bounds and a lower bound for transformers

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

math.OC2025

Glocal Smoothness: Line search and adaptive step sizes can help in theory too!

Curtis Fox, Aaron Mishkin, Sharan Vaswani +1

Iteration complexities for optimizing smooth functions with first-order algorithms are typically stated in terms of a global Lipschitz constant of the gradient, and near-optimal re…

cs.LG2024★ 1 cited

Next-token prediction capacity: general upper bounds and a lower bound for transformers

Liam Madden, Curtis Fox, Christos Thrampoulidis

Given a sequence of tokens, such as words, the task of next-token prediction is to predict the next-token conditional probability distribution. Decoder-only transformers have becom…