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Testing GPT-4 with Wolfram Alpha and Code Interpreter plug-ins on math and science problems

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arxiv 2308.05713 v4 pith:4LCDCIB3 submitted 2023-08-10 cs.AI math.HOphysics.pop-ph

Ernest Davis , Scott Aaronson This is my paper · ORCID
classification cs.AImath.HOphysics.pop-ph
keywords problemsplug-insalphacodefailuresgpt-4interfaceinterpreter
verification ladder T0 review T1 audit T2 compute T3 formal
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This report describes a test of the large language model GPT-4 with the Wolfram Alpha and the Code Interpreter plug-ins on 105 original problems in science and math, at the high school and college levels, carried out in June-August 2023. Our tests suggest that the plug-ins significantly enhance GPT's ability to solve these problems. Having said that, there are still often "interface" failures; that is, GPT often has trouble formulating problems in a way that elicits useful answers from the plug-ins. Fixing these interface failures seems like a central challenge in making GPT a reliable tool for college-level calculation problems.

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Cited by 1 Pith paper

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  1. Evaluation of LLMs for mathematical problem solving

    cs.AI 2025-05 reject novelty 3.0 of 10

    A three-model, three-dataset LLM math evaluation using a multi-dimensional reasoning rubric, undermined by contradictory accuracy tables.

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