Fine-tuned simulators grounded in real human data produce LLM assistants that win more often against real users than those trained against role-playing simulators.
A probabilistic framework for dialog simulation and optimal strategy learning.IEEE Transactions on Audio, Speech, and Language Processing, 14 (2):589–599
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Quantifying the Utility of User Simulators for Building Collaborative LLM Assistants
Fine-tuned simulators grounded in real human data produce LLM assistants that win more often against real users than those trained against role-playing simulators.