Exploring Mobile Touch Interaction with Large Language Models
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arXiv
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| Autores principales: | , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866909488144973824 |
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| author | Zindulka, Tim Sekowski, Jannek Lehmann, Florian Buschek, Daniel |
| author_facet | Zindulka, Tim Sekowski, Jannek Lehmann, Florian Buschek, Daniel |
| contents | Interacting with Large Language Models (LLMs) for text editing on mobile devices currently requires users to break out of their writing environment and switch to a conversational AI interface. In this paper, we propose to control the LLM via touch gestures performed directly on the text. We first chart a design space that covers fundamental touch input and text transformations. In this space, we then concretely explore two control mappings: spread-to-generate and pinch-to-shorten, with visual feedback loops. We evaluate this concept in a user study (N=14) that compares three feedback designs: no visualisation, text length indicator, and length + word indicator. The results demonstrate that touch-based control of LLMs is both feasible and user-friendly, with the length + word indicator proving most effective for managing text generation. This work lays the foundation for further research into gesture-based interaction with LLMs on touch devices. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_07629 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Exploring Mobile Touch Interaction with Large Language Models Zindulka, Tim Sekowski, Jannek Lehmann, Florian Buschek, Daniel Human-Computer Interaction Computation and Language H.5.2; I.2.7 Interacting with Large Language Models (LLMs) for text editing on mobile devices currently requires users to break out of their writing environment and switch to a conversational AI interface. In this paper, we propose to control the LLM via touch gestures performed directly on the text. We first chart a design space that covers fundamental touch input and text transformations. In this space, we then concretely explore two control mappings: spread-to-generate and pinch-to-shorten, with visual feedback loops. We evaluate this concept in a user study (N=14) that compares three feedback designs: no visualisation, text length indicator, and length + word indicator. The results demonstrate that touch-based control of LLMs is both feasible and user-friendly, with the length + word indicator proving most effective for managing text generation. This work lays the foundation for further research into gesture-based interaction with LLMs on touch devices. |
| title | Exploring Mobile Touch Interaction with Large Language Models |
| topic | Human-Computer Interaction Computation and Language H.5.2; I.2.7 |
| url | https://arxiv.org/abs/2502.07629 |