Apple Proposes Token-Level Length Value Model to Optimize Inference Cost
Apple ML Research · rss · 2026-07-20
Apple's machine learning team introduced the Length Value Model (LenVM), a novel framework designed to address how generation length impacts both inference cost and reasoning performance in autoregressive models.
While existing approaches primarily operate at a coarse-grained sequence level, LenVM introduces fine-grained, token-level length modeling. By formulating length modeling as a value estimation problem, the framework predicts the remaining generation length at each decoding step and assigns a constant negative reward to each generated token, enabling more scalable and precise pretraining.
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