Large Language Model (LLM) -based conversational agents have become increasingly popular in recent years due to their novel capacity for natural, human-like dialogue interactions. However, mistrust in LLMs persists due to concerns about privacy, the potential for incorrect responses (often referred to as “hallucinations”), and issues related to social bias. Previous AI research shows that anthropomorphic form positively influences users’ perceptions. However, this aspect remains under-explored in LLM-based conversational agent research. Our research features two anthropomorphic forms: embodied and behavioral. Embodied Anthropomorphic Form (EA) encompasses chatbot, chatbot with Text-to-Speech (TTS) , and Embodied Conversational Agent (ECA) interface designs. Behavioral Anthropomorphic (BA) Form involves LLMs instructed with and without Theory of Mind (ToM) principles. In an empirical evaluation, we explored how interplay between BA form and EA form, and vice-versa, affects users’ perceptions of LLM-based conversational agents on trust, anthropomorphism, presence, usability, and user experience. Our findings provide evidence of such effects, offering novel insight into the influence of both anthropomorphic forms on perceived anthropomorphism, presence, usability, user experience, and their positive impact on user trust in LLM-based conversational agents. However, the combined highest (i.e., ECA with ToM behaviors ) and lowest (i.e., Chatbot without ToM behaviors ) levels of both forms result in lower user trust, suggesting a complex relationship between embodiment and ToM behaviors that warrants further investigation.

Understanding visual attention in users during stressful situations with emotional crowds is crucial for the improvement of emergency response, safety, and efficiency. To explore this, we conducted a study examining how the organizational structure and reaction behavior of a virtual emotional crowd affected subjects' visual attention. Participants completed a task in a virtual reality simulation featuring a fire threat. The experiment employed two between-subjects factors (Crowd Type and Reaction Type) and one within-subjects factor (Simulation Phase). The simulation consisted of a normal phase, where participants interacted with virtual human (VHs) pedestrians and vendors in a virtual marketplace, followed by a stressful phase featuring a fire threat within the same setting. The Crowd Type varied between individuals walking alone (Individual Condition) and small groups of 3-4 members (Group Condition). The Reaction Type determined whether the virtual crowd ignored the threat or moved faster to escape. We analyzed subjects' fixation gaze across conditions, revealing that visual attention behavior was significantly influenced by Crowd Type, Reaction Type, and Simulation Phase.

As virtual reality (VR) technology continues to gain traction as a powerful tool for persuasion and marketing, its application in immersive sales environments has become increasingly relevant. VR’s ability to simulate realistic interactions allows for novel approaches to influencing consumer behavior, particularly through the use of interactive Virtual Humans (VHs). In this study, we investigate the effects of user and virtual human age and gender on persuasion and social influence, via various social psychological factors such as brand attitude, interpersonal attraction, source credibility, and presence. In the process, we conducted a 3 (virtual agent age) × 2 (virtual agent gender) × 3 (module topic) multi-factorial design (N=45). The study included two agent gender conditions, namely gender-matched and gender-mismatched with the user, assigned in a between-subjects manner, and three agent age conditions, namely (1) young adult (20-39), (2) middle-aged adult (40-59), and (3) older adult (60-79). Our findings indicate that the age and gender of virtual humans significantly influence their persuasiveness and social impact, which varies based on the user’s own age and gender. Specifically, virtual humans of a different gender from the user may exhibit higher levels of persuasion and social influence. Furthermore, female and older users appear to be more susceptible to influence compared to male and younger users. Our findings provide novel, critical insights for designing more effective virtual sales strategies and tailoring persuasive technologies to diverse user profiles, thus filling a vital gap in understanding the interaction between user and agent characteristics in virtual environments.1