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View a PDF of the paper titled FutureFill: Quick Technology from Convolutional Sequence Fashions, by Naman Agarwal and 6 different authors
Summary:We handle the problem of environment friendly auto-regressive technology in sequence prediction fashions by introducing FutureFill – a way for quick technology that applies to any sequence prediction algorithm primarily based on convolutional operators. Our strategy reduces the technology time requirement from quadratic to quasilinear relative to the context size. Moreover, FutureFill requires a prefill cache sized solely by the variety of tokens generated, which is smaller than the cache necessities for normal convolutional and attention-based fashions. We validate our theoretical findings with experimental proof demonstrating correctness and effectivity features in an artificial technology activity.
Submission historical past
From: Naman Agarwal [view email]
[v1]
Wed, 2 Oct 2024 15:22:08 UTC (802 KB)
[v2]
Fri, 25 Oct 2024 19:45:33 UTC (2,532 KB)
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#Quick #Technology #Convolutional #Sequence #Fashions
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