代码段
计算机科学
软件工程
代码生成
开源
源代码
编码(集合论)
人工智能
工业工程
系统工程
程序设计语言
工程类
软件
集合(抽象数据类型)
计算机安全
钥匙(锁)
作者
Shuyue Wang,Peng Cao,Xiaotong Yan,Shanwei Mu,Xuelian Yu,Xuan Wang
标识
DOI:10.1145/3660395.3660411
摘要
With huge progress in Large Language Model (LLM) by Artificial-Intelligence-Generated-Content (AIGC), a technical demand from the industry of autodriving with respect to scenario generation needs sees a new possible solution. Thus a new powerful tools of computational modeling, and simulation is now at hand. In this paper, we explore the use of prompt engineering and the fine-tuning applied to open-source model. This paper studies the use about OpenSCENARIO. The theoretical descriptions comes with practical experiment in comparisons of prompt feedbacks and performance estimation of long conceptual Q&A and code snippet generation.
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