MenuCraft: Interactive Menu System Design with Large Language Models
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866910516677443584 |
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| author | Kargaran, Amir Hossein Nikeghbal, Nafiseh Heydarnoori, Abbas Schütze, Hinrich |
| author_facet | Kargaran, Amir Hossein Nikeghbal, Nafiseh Heydarnoori, Abbas Schütze, Hinrich |
| contents | Menu system design for user interfaces is a challenging task involving many design options and various human factors. For example, one crucial factor that designers need to consider is the semantic and systematic relation of menu commands. However, capturing these relations can be challenging due to limited available resources. Large language models can be helpful in this regard, using their pre-training knowledge to design and refine menu systems. In this paper, we propose MenuCraft, an AI-assisted designer for menu design that enables collaboration between the designer and a dialogue system to design menus. MenuCraft offers an interactive language-based menu design tool that simplifies the menu design process and enables easy customization of design options. MenuCraft supports a variety of interactions through dialog that allows performing in-context learning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_04496 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | MenuCraft: Interactive Menu System Design with Large Language Models Kargaran, Amir Hossein Nikeghbal, Nafiseh Heydarnoori, Abbas Schütze, Hinrich Computation and Language Artificial Intelligence Human-Computer Interaction Menu system design for user interfaces is a challenging task involving many design options and various human factors. For example, one crucial factor that designers need to consider is the semantic and systematic relation of menu commands. However, capturing these relations can be challenging due to limited available resources. Large language models can be helpful in this regard, using their pre-training knowledge to design and refine menu systems. In this paper, we propose MenuCraft, an AI-assisted designer for menu design that enables collaboration between the designer and a dialogue system to design menus. MenuCraft offers an interactive language-based menu design tool that simplifies the menu design process and enables easy customization of design options. MenuCraft supports a variety of interactions through dialog that allows performing in-context learning. |
| title | MenuCraft: Interactive Menu System Design with Large Language Models |
| topic | Computation and Language Artificial Intelligence Human-Computer Interaction |
| url | https://arxiv.org/abs/2303.04496 |