Making Large Language Models More Reliable and Beneficial: Taking ChatGPT as a Case Study

COMPUTER（2024）

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摘要

This article suggests practical ways to make large language models more reliable and beneficial by taking ChatGPT as a case study. Specifically, we describe ChatGPT's workflow and promised services and highlight the perils requiring the immediate attention of ChatGPT stakeholders.

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Large language models,Reliability engineering,Chatbots,Artificial intelligence,Human factors,Open systems,Deep learning,Context awareness,Question answering (information retrieval),Market research,Technology forecasting,Modeling,Stakeholders

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