SearcharxivSearch

arXiv subjects

Songchen Zhou

Publications and source records attributed to Songchen Zhou.

2 recordsLinked to original sources

Observable Social Life Spaces: Exploring User Interpretations of agent-side life context in human-agent interaction

Many AI agents are organized around instrumental "command-execution" interactions, where users primarily encounter agents through task requests and responses. Recent work on generative agents and agent life worlds has drawn attention to agents that maintain social contexts beyond direct user commands. In this paper, we study how observable social life spaces shape users' subjective experience, relational interpretations, and perceived equality during human-agent interaction. We introduce the \textit{Observable Social Life Spaces} paradigm, where agents inhabit a continuous virtual environment, engage in daily activities, and form social relationships that users can directly observe. Through an exploratory mixed-methods study ($N=24$), we found that the Observable condition yielded higher perceived-equality ratings and more frequent equality-related role descriptions than the Baseline and Unobservable conditions, but participant-level analysis suggests that the quantitative effect should be interpreted cautiously. We discuss perceived equality as a user-perception signal shaped by this design, with attention to boundary conditions including visual richness, novelty, and person-like attribution from visible agent cues.

cs.HC

Augmented Body Communicator: Enhancing daily body expression for people with upper limb limitations through LLM and a robotic arm

Individuals with upper limb movement limitations face challenges in interacting with others. Although robotic arms are currently used primarily for functional tasks, there is considerable potential to explore ways to enhance users' body language capabilities during social interactions. This paper introduces an Augmented Body Communicator system that integrates robotic arms and a large language model. Through the incorporation of kinetic memory, disabled users and their supporters can collaboratively design actions for the robot arm. The LLM system then provides suggestions on the most suitable action based on contextual cues during interactions. The system underwent thorough user testing with six participants who have conditions affecting upper limb mobility. Results indicate that the system improves users' ability to express themselves. Based on our findings, we offer recommendations for developing robotic arms that support disabled individuals with body language capabilities and functional tasks.

cs.HC