ComputeGPT: A computational chat model for numerical problems
Ryan Hardesty Lewis Junfeng Jiao
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.