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arXiv 2409.11232cs.CLcond-mat.dis-nncs.AI
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OpenAI O1-Preview模型在求解随机K-SAT问题中的快速分析:LLM是自行求解还是调用外部SAT求解器?

Fast Analysis of the OpenAI O1-Preview Model in Solving Random K-SAT Problem: Does the LLM Solve the Problem Itself or Call an External SAT Solver?

University of Florence(佛罗伦萨大学)

Raffaele Marino

AI总结:

本文分析了OpenAI O1-preview模型在求解随机K-SAT问题时的表现,发现其通过调用外部SAT求解器而非直接求解,且输出常含错误赋值,并提出方法量化其展现智能火花还是随机猜测。

摘要:

在本文中,我分析了OpenAI O1-preview模型在求解K∈{2,3,4}的随机K-SAT实例时的性能,该性能表示为α=M/N的函数,其中M是可满足问题的子句数,N是变量数。我证明该模型会调用外部SAT求解器来求解实例,而不是直接求解。尽管使用了外部求解器,模型仍将错误的赋值作为输出报告。此外,我提出并展示了一项分析,以量化OpenAI O1-preview模型在为布尔可满足性问题输出赋值时,是展现出智能火花还是仅进行随机猜测。

英文摘要:

In this manuscript, I present an analysis on the performance of OpenAI O1-preview model in solving random K-SAT instances for K$\in {2,3,4}$ as a function of $α=M/N$ where $M$ is the number of clauses and $N$ is the number of variables of the satisfiable problem. I show that the model can call an external SAT solver to solve the instances, rather than solving them directly. Despite using external solvers, the model reports incorrect assignments as output. Moreover, I propose and present an analysis to quantify whether the OpenAI O1-preview model demonstrates a spark of intelligence or merely makes random guesses when outputting an assignment for a Boolean satisfiability problem.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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