PGHS fuses policy-guided LLM reasoning and ML fitting to simulate group user behavior with 8.8% error on Meituan data from 101 merchants and 26k trajectories, beating pure reasoning and fitting baselines by 45.8% and 40.9%.
Dullerud, Peter J
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The paper proposes a bidirectional continuum between LLMs and control systems, covering LLM-assisted controller design, control-based LLM steering, and state-space modeling of LLMs.
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Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation
PGHS fuses policy-guided LLM reasoning and ML fitting to simulate group user behavior with 8.8% error on Meituan data from 101 merchants and 26k trajectories, beating pure reasoning and fitting baselines by 45.8% and 40.9%.
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When control meets large language models: From words to dynamics
The paper proposes a bidirectional continuum between LLMs and control systems, covering LLM-assisted controller design, control-based LLM steering, and state-space modeling of LLMs.