[2603.26922] Mimetic Alignment with ASPECT: Evaluation of AI-inferred Personal Profiles

Computer Science > Human-Computer Interaction arXiv:2603.26922 (cs) [Submitted on 27 Mar 2026] Title:Mimetic Alignment with ASPECT: Evaluation of AI-inferred Personal Profiles Authors:Ruoxi Shang, Dan Marshall, Edward Cutrell, Denae Ford View a PDF of the paper titled Mimetic Alignment with ASPECT: Evaluation of AI-inferred Personal Profiles, by Ruoxi Shang and 3 other authors View PDF HTML (experimental) Abstract:AI agents that communicate on behalf of individuals need to capture how each person actually communicates, yet current approaches either require costly per-person fine-tuning, produce generic outputs from shallow persona descriptions, or optimize preferences without modeling communication style. We present ASPECT (Automated Social Psychometric Evaluation of Communication Traits), a pipeline that directs LLMs to assess constructs from a validated communication scale against behavioral evidence from workplace data, without per-person training. In a case study with 20 participants (1,840 paired item ratings, 600 scenario evaluations), ASPECT-generated profiles achieved moderate alignment with self-assessments, and ASPECT-generated responses were preferred over generic and self-report baselines on aggregate, with substantial variation across individuals and scenarios. During the profile review phase, linked evidence helped participants identify mischaracterizations, recalibrate their own self-ratings, and negotiate context-appropriate representations. We discuss impl...