From Specifications to Prompts: On the Future of Generative LLMs in Requirements Engineering
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arXiv
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910569287647232 |
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| author | Vogelsang, Andreas |
| author_facet | Vogelsang, Andreas |
| contents | Generative LLMs, such as GPT, have the potential to revolutionize Requirements Engineering (RE) by automating tasks in new ways. This column explores the novelties and introduces the importance of precise prompts for effective interactions. Human evaluation and prompt engineering are essential in leveraging LLM capabilities. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_09127 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | From Specifications to Prompts: On the Future of Generative LLMs in Requirements Engineering Vogelsang, Andreas Software Engineering Generative LLMs, such as GPT, have the potential to revolutionize Requirements Engineering (RE) by automating tasks in new ways. This column explores the novelties and introduces the importance of precise prompts for effective interactions. Human evaluation and prompt engineering are essential in leveraging LLM capabilities. |
| title | From Specifications to Prompts: On the Future of Generative LLMs in Requirements Engineering |
| topic | Software Engineering |
| url | https://arxiv.org/abs/2408.09127 |