Beyond Turn-taking: Introducing Text-based Overlap into Human-LLM Interactions

JiWoo Kim; Minsuk Chang; JinYeong Bak

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arXiv · 2501.18103

Beyond Turn-taking: Introducing Text-based Overlap into Human-LLM Interactions

JiWoo Kim·Minsuk Chang·JinYeong Bak

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Abstract

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.

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JiWoo Kim, Minsuk Chang, JinYeong Bak. 2025-01-30. Beyond Turn-taking: Introducing Text-based Overlap into Human-LLM Interactions. https://arxiv.org/abs/2501.18103

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