ChatGPT 失败案例的分类档案
A Categorical Archive of ChatGPT Failures
AI总结：
本研究针对 ChatGPT 缺乏失败案例分析的问题，系统提出并讨论了包括推理、事实错误、数学、编码和偏见等十一类失败案例，旨在帮助研究人员和开发者改进未来的语言模型与聊天机器人。
摘要：
大型语言模型已被证明在不同领域具有价值。由 OpenAI 开发的 ChatGPT 使用海量数据进行训练，通过理解上下文和生成适当的回应来模拟人类对话。它因能有效回答广泛的人类询问而备受关注，其流畅且全面的回答在安全性和实用性上均超越了先前的公共聊天机器人。然而，目前缺乏对 ChatGPT 失败案例的全面分析，这正是本研究的重点。本文提出并讨论了十一类失败案例，包括推理、事实错误、数学、编码和偏见。此外，还强调了 ChatGPT 的风险、局限性和社会影响。本研究的目标是协助研究人员和开发人员改进未来的语言模型和聊天机器人。
英文摘要：
Large language models have been demonstrated to be valuable in different fields. ChatGPT, developed by OpenAI, has been trained using massive amounts of data and simulates human conversation by comprehending context and generating appropriate responses. It has garnered significant attention due to its ability to effectively answer a broad range of human inquiries, with fluent and comprehensive answers surpassing prior public chatbots in both security and usefulness. However, a comprehensive analysis of ChatGPT's failures is lacking, which is the focus of this study. Eleven categories of failures, including reasoning, factual errors, math, coding, and bias, are presented and discussed. The risks, limitations, and societal implications of ChatGPT are also highlighted. The goal of this study is to assist researchers and developers in enhancing future language models and chatbots.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
