A Three-Tier Persona Vector for Controllable User Simulation in Agentic Evaluation

Rahul Khedar; Eshita; Sneha Teja Sree Reddy Thondapu; Mayank Malhotra; Arup Kumar Das; Jitesh Chandra Mishra; Arun Menon; Avinash Karn; Mouli V

arXiv · 2609.08592

A Three-Tier Persona Vector for Controllable User Simulation in Agentic Evaluation

Rahul Khedar·Eshita·Sneha Teja Sree Reddy Thondapu·Mayank Malhotra·Arup Kumar Das·Jitesh Chandra Mishra·Arun Menon·Avinash Karn·Mouli V

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Abstract

Evaluating tool-augmented LLM agents requires diverse, realistic user inputs yet most evaluation frameworks use flat role descriptions ("you are an angry customer") that produce near-identical conversations regardless of the underlying scenario. In this paper, we propose a three-tier persona vector with 23 operationalized dimensions: 6 categorical demographics (jurisdiction, age, channel, device, language proficiency, time availability), 12 continuous behavioral traits (patience, assertiveness, digital literacy, etc.) sampled with Gaussian noise around curated profile base vectors, and 5 continuous emotional states (frustration, anxiety, trust, confidence, stress) that shift in response to scenario context. Orthogonal to the persona, a 4-level query-complexity overlay controls utterance phrasing from direct to deliberately vague. We evaluate the persona model inside a synthetic data generation pipeline across 64,698 multi-turn conversations spanning 8 named profiles and 3 production corpora. Key findings: (i) a 15.8 percentage-point spread in agent goal-achievement across personas confirms trait vectors produce measurably different user behavior; (ii) the same persona behaves differently across scenarios due to scenario-reactive emotional state shifts, validating the scenario-reactive design; (iii) domain-specific projects show persona sensitivity on booking-flow compliance (~15-20 percentage points gap between tier-aware and pressure-test personas), demonstrating the model faithfully reproduces real-world difficulty distributions; (iv) seven rule-described trait correlations produce auditable co-occurrence patterns without requiring learned covariance matrices. The persona model is fully specified for reproduction.

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Rahul Khedar, Eshita, Sneha Teja Sree Reddy Thondapu, Mayank Malhotra, Arup Kumar Das, Jitesh Chandra Mishra, Arun Menon, Avinash Karn, Mouli V. 2026-09-08. A Three-Tier Persona Vector for Controllable User Simulation in Agentic Evaluation. https://arxiv.org/abs/2609.08592

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