Towards using Few-Shot Prompt Learning for Automating Model Completion

• URL: http://arxiv.org/abs/2212.03404v1
• Date: Wed, 7 Dec 2022 02:11:26 GMT
• Title: Towards using Few-Shot Prompt Learning for Automating Model Completion
• Authors: Meriem Ben Chaaben and Lola Burgue\~no and Houari Sahraoui
• Abstract summary: We propose a simple yet a novel approach to improve completion in domain modeling activities. Our approach exploits the power of large language models by using few-shot prompt learning without the need to train or fine-tune those models.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: We propose a simple yet a novel approach to improve completion in domain modeling activities. Our approach exploits the power of large language models by using few-shot prompt learning without the need to train or fine-tune those models with large datasets that are scarce in this field. We implemented our approach and tested it on the completion of static and dynamic domain diagrams. Our initial evaluation shows that such an approach is effective and can be integrated in different ways during the modeling activities.

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