Learning User Representations to Improve Simulation Fidelity
User simulators enable interactive training and evaluation of AI assistants at scale. Yet current simulators struggle to reproduce the diverse behaviors of real users, leading to assistants that generalize poorly to underrepresented users.
By Shuhaib Mehri, Philippe Laban, Michel Galley, Dilek T\"ur, Jennifer Neville, Jianfeng GaoarXiv - cs.CL (NLP)
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Originally published by arXiv - cs.CL (NLP) on Oct 19, 2026.
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