arXiv subjects

Shao-Kang Hsia

Publications and source records attributed to Shao-Kang Hsia.

3 recordsLinked to original sources

arXiv2026

Towards Natural Language Environment: Understanding Seamless Natural-Language-Based Human-Multi-Robot Interactions

As multiple robots are expected to coexist in future households, natural language is increasingly envisioned as a primary medium for human-robot and robot-robot communication. This paper introduces the concept of a Natural Language Environment (NLE), defined as an interaction space in which humans and multiple heterogeneous robots coordinate primarily through natural language. Rather than proposing a deployable system, this work aims to explore the design space of such environments. We first synthesize prior work on language-based human-robot interaction to derive a preliminary design space for NLEs. We then conduct a role-playing study in virtual reality to investigate how people conceptualize, negotiate, and coordinate human-multi-robot interactions within this imagined environment. Based on qualitative and quantitative analysis, we refine the preliminary design space and derive design implications that highlight key tensions and opportunities around task coordination dominance, robot autonomy, and robot personality in Natural Language Environments.

cs.HC↗

arXiv2025

GesPrompt: Leveraging Co-Speech Gestures to Augment LLM-Based Interaction in Virtual Reality

Large Language Model (LLM)-based copilots have shown great potential in Extended Reality (XR) applications. However, the user faces challenges when describing the 3D environments to the copilots due to the complexity of conveying spatial-temporal information through text or speech alone. To address this, we introduce GesPrompt, a multimodal XR interface that combines co-speech gestures with speech, allowing end-users to communicate more naturally and accurately with LLM-based copilots in XR environments. By incorporating gestures, GesPrompt extracts spatial-temporal reference from co-speech gestures, reducing the need for precise textual prompts and minimizing cognitive load for end-users. Our contributions include (1) a workflow to integrate gesture and speech input in the XR environment, (2) a prototype VR system that implements the workflow, and (3) a user study demonstrating its effectiveness in improving user communication in VR environments.

cs.HC↗

arXiv2025

Investigating Creativity in Humans and Generative AI Through Circles Exercises

Generative AI (GenAI) is transforming the creativity process. However, as presented in this paper, GenAI encounters "narrow creativity" barriers. We observe that both humans and GenAI focus on limited subsets of the design space. We investigate this phenomenon using the "Circles Exercise," a creativity test widely used to examine the creativity of humans. Quantitative analysis reveals that humans tend to generate familiar, high-frequency ideas, while GenAI produces a larger volume of incremental innovations at a low cost. However, similar to humans, it struggles to significantly expand creative boundaries. Moreover, advanced prompting strategies, such as Chain-of-Thought (CoT) prompting, mitigate narrow creativity issues but still fall short of substantially broadening the creative scope of humans and GenAI. These findings underscore both the challenges and opportunities for advancing GenAI-powered human creativity support tools.

cs.HC↗