3 papers
cs.CL2026
CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators
Yada Pruksachatkun, Yixin Wan, Elaine Wan +4
We present CustomerSim, an environment and benchmark to evaluate the extent to which Multimodal Large Language Models (MLLMs) can simulate realistic, persona-driven customer behavi…
cs.CL2026
The Need for a Socially-Grounded Persona Framework for User Simulation
Pranav Narayanan Venkit, Yu Li, Yada Pruksachatkun +1
Synthetic personas are widely used to condition large language models (LLMs) for social simulation, yet most personas are still constructed from coarse sociodemographic attributes…
cs.HC2025
Proactive Conversational Agents with Inner Thoughts
Xingyu Bruce Liu, Shitao Fang, Weiyan Shi +3
One of the long-standing aspirations in conversational AI is to allow them to autonomously take initiatives in conversations, i.e., being proactive. This is especially challenging…