Sep 2026· Adjunct Proceedings of the 18th International Conference on Automotive User Interfaces and Interactive Vehicular Applications· pp. 183-187· 0 citations· 14 references
Abstract
This Work-in-Progress examines whether personality-informed prompting changes perceived LLM emotional support in driving scenarios designed to elicit stress. A condition-order-balanced, within-subject CARLA simulator study (n = 14) compared a baseline with a Driver Personality Profile (DPP) condition; a supplementary online video pilot (n = 12) examined response perception without driving control or live-system latency. No statistically detectable condition differences emerged for usefulness, ease of use, privacy concerns, or social/emotional presence, and only 7 of 14 simulator participants identified the DPP condition correctly. A post-hoc lexical audit showed that both conditions frequently reused generic supportive scaffolding. We discuss output anchoring as one tentative interpretation, not an established phenomenon: the evidence cannot distinguish constraint-dominated generation from a weak personalization manipulation or limitations of the 7B model. The findings motivate stronger, independently validated personalization manipulations and privacy-aware in-vehicle support.
LLM-based conversational agents generate fluent responses but remain limited in adapting their supportive style to individual personality and emotional needs. We present a Detect–Regulate–Evaluate (D–R–E) architecture that performs turn-by-turn Big Five detection and applies Zurich Model-inspired behavioural regulation...
Duojie Jiahua, Samuel Devdas, Mirjam Stieger et al.· Electronics· 0 citations
Large language models are increasingly consulted at moments of distress, yet single-turn benchmarks neither test sustained exchanges nor distinguish between users. We built a personality-aware evaluation in which four widely used models advised several synthetic help-seekers, each given a psychometrically specified pro...
P. Fonseca, R. Rodríguez-Carvajal, Rafael A. Calvo· 0 citations
Despite growing interest in prompt engineering, its influence on user experience—particularly in relation to cultural communication norms—remains largely unexplored. This controlled experiment examined how respectful versus directive prompting—a culturally meaningful contrast in Korean—affects Korean users’ psychologic...
Digital health interventions often rely on static message templates for health behaviour support, which can struggle to sustain engagement over time. Large language models (LLMs) offer a promising alternative by enabling context-sensitive message generation with personality-trait-based language adaptation across repeat...
Dominik P. Hofer, David Haag, R. Islambouli et al.· Message Understanding Confer...· 0 citations
Platform policies are increasingly tested on artificial users, making agent fidelity important. Yet convincing fake profiles could also manipulate perceived public opinion before elections. Validation has concentrated on agreement with human behaviour and has paid little attention to whether an agent behaves in line wi...
Ljubiša Bojić, Tijana Stanić, Joerg Matthes et al.· 0 citations
The findings suggest that fit, helpfulness, and structural safety are separable design problems, and that coherent supporter identity can help address all three.
Ben Wigler, M. Tsfasman· Proceedings of the 26th ACM...· 0 citations
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