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English(EN) I'm tentatively understanding the news about LLMs offering barely comprehensible solutions to hundreds of hard maths problems in the following way. # Maths is s

LLMs通过符号操作解决数学难题,但缺乏真正理解

大型语言模型(LLMs)可以通过将数学视为一种基于规则的符号操作任务来解决复杂的数学问题。这种方法允许LLMs生成解决方案,例如Python代码,而不一定理解潜在的数学概念。该过程依赖于在大量数学文本上训练模型以学习这些符号规则。 AI

影响 这种观点表明,即使没有深入的理解,LLMs也可能通过模仿基于规则的系统在形式化任务上表现出色。

排序理由 该条目讨论了LLMs如何解决数学问题的概念性理解,而不是宣布新的模型或研究发现。

在 Mastodon — fosstodon.org 阅读 →

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LLMs通过符号操作解决数学难题,但缺乏真正理解

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3 / 100
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该条目讨论了LLMs如何解决数学问题的概念性理解,而不是宣布新的模型或研究发现。
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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paper
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High
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Breaking (< 6h)
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报道来源 [1]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    我正在初步理解有关大型语言模型(LLM)为数百个难题提供勉强可理解的数学解法的新闻。#数学是s

    I'm tentatively understanding the news about LLMs offering barely comprehensible solutions to hundreds of hard maths problems in the following way. # Maths is symbol manipulation according to set rules. You can do this task by training an LLM on a lot of maths writing. You don't …