Beyond Turn-taking: Introducing Text-based Overlap into Human-LLM Interactions
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866913671000621056 |
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| author | Kim, JiWoo Chang, Minsuk Bak, JinYeong |
| author_facet | Kim, JiWoo Chang, Minsuk Bak, JinYeong |
| contents | Traditional text-based human-AI interactions often adhere to a strict turn-taking approach. In this research, we propose a novel approach that incorporates overlapping messages, mirroring natural human conversations. Through a formative study, we observed that even in text-based contexts, users instinctively engage in overlapping behaviors like "A: Today I went to-" "B: yeah." To capitalize on these insights, we developed OverlapBot, a prototype chatbot where both AI and users can initiate overlapping. Our user study revealed that OverlapBot was perceived as more communicative and immersive than traditional turn-taking chatbot, fostering faster and more natural interactions. Our findings contribute to the understanding of design space for overlapping interactions. We also provide recommendations for implementing overlap-capable AI interactions to enhance the fluidity and engagement of text-based conversations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_18103 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Beyond Turn-taking: Introducing Text-based Overlap into Human-LLM Interactions Kim, JiWoo Chang, Minsuk Bak, JinYeong Human-Computer Interaction Computation and Language Traditional text-based human-AI interactions often adhere to a strict turn-taking approach. In this research, we propose a novel approach that incorporates overlapping messages, mirroring natural human conversations. Through a formative study, we observed that even in text-based contexts, users instinctively engage in overlapping behaviors like "A: Today I went to-" "B: yeah." To capitalize on these insights, we developed OverlapBot, a prototype chatbot where both AI and users can initiate overlapping. Our user study revealed that OverlapBot was perceived as more communicative and immersive than traditional turn-taking chatbot, fostering faster and more natural interactions. Our findings contribute to the understanding of design space for overlapping interactions. We also provide recommendations for implementing overlap-capable AI interactions to enhance the fluidity and engagement of text-based conversations. |
| title | Beyond Turn-taking: Introducing Text-based Overlap into Human-LLM Interactions |
| topic | Human-Computer Interaction Computation and Language |
| url | https://arxiv.org/abs/2501.18103 |