Experimental results from applying GPT-4 to an unpublished formal language

• URL: http://arxiv.org/abs/2305.12196v1
• Date: Sat, 20 May 2023 14:00:08 GMT
• Title: Experimental results from applying GPT-4 to an unpublished formal language
• Authors: Gregor vom Scheidt
• Abstract summary: A state-of-the-art system, GPT-4, was provided with a concise natural language specification for a previously unpublished formal system. The system completed all tasks successfully, showed extensive domain knowledge, invented helpful new syntax and semantics, and exhibited generalization and inference abilities.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Can large language models be used to complete mathematical tasks that are traditionally performed either manually or with the aid of theorem provers? To answer this question, a state-of-the-art system, GPT-4, was provided with a concise natural language specification for a previously unpublished formal system and asked to complete a number of tasks, from stating function and type definitions to proving simple theorems and verifying user-supplied proofs. The system completed all tasks successfully, showed extensive domain knowledge, invented helpful new syntax and semantics, and exhibited generalization and inference abilities. So the answer seems to be: yes.

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