ComputeGPT: A computational chat model for numerical problems
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Abstract (arXiv)
Language models are not accurate in numerical problems. Their architecture does not allow for anything less than a probabilistic next word. This paper introduces ComputeGPT: an approach of creating a chat model able to answer computational problems through running on-demand code. ComputeGPT converts each question to relevant code, runs the code, and returns the computed answer as part of the chat. We combine this approach with a local browser-based Python interpretation and fine-tuned prompts in order to achieve state-of-the-art efficiency on numerical problems and provide a suitable front-end and safe environment for the code to be executed in.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 15 of its 40 references that are in the map. First posted on arXiv 8 May 2023.
Builds on
15 of 40 references.
References · 15
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Citing papers per year: 2023: 1.
1 paper.