回到信息流
论文更新 / THE SIGNAL

Arithmetic and its remedies select the evidence on learned geometry

来源原文

来源简介

arXiv:2607.17513v2 Announce Type: replace-cross Abstract: Intelligence that must act before outside correction arrives must carry the structure of its expert knowledge, and hyperbolic geometry represents hierarchy with a fidelity no Euclidean space of comparable dimension matches. Yet hyperbolic language models confine that geometry to adapters or rebuild the transformer, and an independent audit of released hyperbolic vision language checkpoints finds their hierarchy mechanisms inactive, which has been read as evidence about the geometry or its objective. Here we show that it is also evidence about arithmetic. The constraint defining the manifold is a difference of two terms that grow together; for the unclamped map at unit curvature and temperature it fails in every format we measured, double precision included, at the norms standard language models produce in their deepest layers, beyond the limit previously derived. A common remedy, a norm bound, leaves the executed map no radial sensitivity where it acts. In a prespecified test, a tighter bound cost a Lorentz system more of the held out structure it started with than a flat one. Structural supervision has run in six expert systems over 20,951,552 training exposures. In paired runs with a published recipe's objective held fixed, removing its starting scale remedy prevented every update and removing its single precision regions raised the radius reached early in training. Arithmetic bounds the computable region, and within it, alongside the objective, arithmetic and its remedies select which runs leave a record and the states they reach on the way, so a flat surviving checkpoint cannot by itself establish that the geometry is inert.

本条尚未生成中文 AI 摘要,以上展示来源提供的原始简介。
采集于 2026/10/20 21:06:31(北京时间)。 arXiv 日期为本次公告时间,论文初次投稿日期请查看原文版本记录。

阅读 arXiv · cs.CL 原文arxiv.org · 在新窗口打开