自生:个性化的大型语言模型用于学术提升 - - 伦理学和原则证明
Sebastian Porsdam Mann1, Brian D Earp1, Nikolaj Møller1
1University of Oxford.
The American journal of bioethics : AJOB
|July 24, 2023
概括
对个人写作进行微调的大型语言模型,称为AUTOGEN (AI独特定制输出生成器),增强学术散文和创意生成. 这些个性化的模型显示,如果解决道德考虑,学术提升是有前途的.
科学领域:
- 人工智能的人工智能
- 学术传播学术交流
- 自然语言处理自然语言处理.
背景情况:
- 大型语言模型 (LLM) 为学术写作提供了潜在的帮助.
- 用作者自己的作品来个性化LLM可以根据个人风格和需求量身定制输出.
研究的目的:
- 探索微调个人学术著作的LLM的有效性,用于学术散文和创意产生.
- 开发和评估AUTOGEN (AI独特定制输出发生器) 模型.
主要方法:
- 通过对三个作者的个人和联合先前出版物进行微调GPT-3开发了四个AUTOGEN模型.
- 对质量,风格,格式和创新想法生成的基础GPT-3进行模型性能评估.
主要成果:
- AUTOGEN 模型的输出变异性比基 GPT-3 的输出变异性更大,许多实例的性能都超过了它.
- 通过个性化的法学士课程,证明了增强散文,风格和创新想法生成的潜力.
- 确定了伦理机会 (生产力,风格保存) 和问题 (减少多样性,隐私,抄袭).
结论:
- 像AUTOGEN这样的个性化LLM为学术散文和创意产生提供了显著的好处.
- 解决与隐私,归因和输出多样性相关的伦理挑战对于负责任的实施至关重要.
- 与其他LLM的整合可能会进一步完善学术写作援助.
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