# Generating Diverse Personas for User Simulators to Test Interview Dialogue Systems

arXiv: https://arxiv.org/abs/2608.19549 · HTML: https://mlsanity.com/paper/2608.19549/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 126 references that are in the map.
- First posted on arXiv 20 Aug 2026.

## Builds on (most cited first, 14 of 14)

- [Personalizing Dialogue Agents: I have a dog, do you have pets too?](https://mlsanity.com/paper/1801.07243/) (2018)
- [Scaling Synthetic Data Creation with 1,000,000,000 Personas](https://mlsanity.com/paper/2406.20094/) (2024)
- [PersonaLLM: Investigating the Ability of Large Language Models to Express Personality Traits](https://mlsanity.com/paper/2305.02547/) (2023)
- [Training Millions of Personalized Dialogue Agents](https://mlsanity.com/paper/1809.01984/) (2018)
- [A User Simulator for Task-Completion Dialogues](https://mlsanity.com/paper/1612.05688/) (2016)
- [Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System](https://mlsanity.com/paper/2306.09821/) (2023)
- [DuetSim: Building User Simulator with Dual Large Language Models for Task-Oriented Dialogues](https://mlsanity.com/paper/2405.13028/) (2024)
- [In-Context Learning User Simulators for Task-Oriented Dialog Systems](https://mlsanity.com/paper/2306.00774/) (2023)
- [Leveraging Large Language Models for Automated Dialogue Analysis](https://mlsanity.com/paper/2309.06490/) (2023)
- [Dialogue Language Model with Large-Scale Persona Data Engineering](https://mlsanity.com/paper/2412.09034/) (2024)
- [Telephone Surveys Meet Conversational AI: Evaluating a LLM-Based Telephone Survey System at Scale](https://mlsanity.com/paper/2502.20140/) (2025)
- [An Automated Testing Framework for Conversational Agents](https://mlsanity.com/paper/1902.06193/) (2019)
- [A Career Interview Dialogue System using Large Language Model-based Dynamic Slot Generation](https://mlsanity.com/paper/2412.16943/) (2024)
- [User Review Writing via Interview with Dialogue Systems](https://mlsanity.com/paper/2603.07070/) (2026)

## Abstract (arXiv)

This paper addresses the issue of the significant labor required to test interview dialogue systems. While interview dialogue systems are expected to be useful in various scenarios, like other dialogue systems, testing them with human users requires significant effort and cost. Therefore, testing with user simulators can be beneficial. Since most conventional user simulators have been primarily designed for training task-oriented dialogue systems, little attention has been paid to the personas of the simulated users. During development, testing interview dialogue systems requires simulating a wide range of user behaviors, but manually creating a large number of personas is labor-intensive. We propose a method that automatically generates personas for user simulators using a large language model. Furthermore, by assigning personality traits related to communication styles when generating personas, we aim to increase the diversity of communication styles in the user simulator. Experimental results show that the proposed method enables the user simulator to generate utterances with greater variation.