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cs.CL2026
CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators
Yada Pruksachatkun, Yixin Wan, Xingrun Chen +2
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.CL2024
Granular Change Accuracy: A More Accurate Performance Metric for Dialogue State Tracking
Taha Aksu, Nancy F. Chen
Current metrics for evaluating Dialogue State Tracking (DST) systems exhibit three primary limitations. They: i) erroneously presume a uniform distribution of slots throughout the…