Related papers: Consistency Analysis of ChatGPT

Consistency Analysis of ChatGPT

URL: http://arxiv.org/abs/2303.06273v3
Date: Tue, 14 Nov 2023 00:20:20 GMT
Title: Consistency Analysis of ChatGPT
Authors: Myeongjun Erik Jang, Thomas Lukasiewicz
Abstract summary: This paper investigates the trustworthiness of ChatGPT and GPT-4 regarding logically consistent behaviour. Our findings suggest that while both models appear to show an enhanced language understanding and reasoning ability, they still frequently fall short of generating logically consistent predictions.
Score: 65.268245109828
License: http://creativecommons.org/licenses/by-nc-sa/4.0/
Abstract: ChatGPT has gained a huge popularity since its introduction. Its positive aspects have been reported through many media platforms, and some analyses even showed that ChatGPT achieved a decent grade in professional exams, adding extra support to the claim that AI can now assist and even replace humans in industrial fields. Others, however, doubt its reliability and trustworthiness. This paper investigates the trustworthiness of ChatGPT and GPT-4 regarding logically consistent behaviour, focusing specifically on semantic consistency and the properties of negation, symmetric, and transitive consistency. Our findings suggest that while both models appear to show an enhanced language understanding and reasoning ability, they still frequently fall short of generating logically consistent predictions. We also ascertain via experiments that prompt designing, few-shot learning and employing larger large language models (LLMs) are unlikely to be the ultimate solution to resolve the inconsistency issue of LLMs.

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