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使用大型语言模型创建叙事事件.
Valentina Bartalesi1, Emanuele Lenzi1,2, Claudio De Martino1
1Institute of Information Science and Technologies "Alessandro Faedo"-ISTI, National Research Council of Italy (CNR), Pisa, Italy.
PeerJ. Computer science
|December 9, 2024
概括
大型语言模型 (LLM) 可以从文本数据中生成可靠的科学叙述. LLaMA 2擅长创造叙事事件,增强知识发现和科学交流.
科学领域:
- 人工智能的人工智能
- 语义网络技术 语义网络技术
- 科学沟通科学沟通
背景情况:
- 叙述对于传达复杂的科学信息和知识至关重要.
- 科学界利用叙事来解释现象和分享见解.
- 将人工智能集成到科学工作流中可以增强数据解释和知识传播.
研究的目的:
- 探索大型语言模型 (LLM) 与语义网络技术的整合,以将原始科学数据转化为叙述.
- 调查LLM在自动生成科学文本可靠的叙事事件的能力.
- 评估各种LLM在维护原始科学叙述的完整性和准确性的表现.
主要方法:
- 叙事事件的概念定义.叙事事件的概念定义.
- 在5个科学叙述的集体上对较小的LLMs进行评估.
- 在124个叙述的更大数据集上对LLM的绩效评估.
- 快速工程技术的应用以优化LLM的性能.
主要成果:
- LLaMA 2在生成准确反映输入科学文本的叙事事件方面表现出卓越的表现.
- 该研究证实了使用LLM自动创建叙事事件的可行性,同时保持文本可靠性.
- 快速工程进一步提高了LLM产生的科学叙事的质量和真实性.
结论:
- 实际上,LLMs,特别是LLaMA 2,可以有效地集成到工作流程中,以生成可靠的科学叙述.
- 这种方法增强了科学社区内知识发现和沟通的过程.
- 该方法确保了原始叙述的完整性,这对于科学准确性和专家审查至关重要.


