SILIC uses LLM-guided inverse reinforcement learning and Theory of Planned Behavior chain reasoning to infer age, gender, income, and employment from travel trajectories, reportedly beating SVM, XGBoost, CatBoost, and GPT-4o baselines.
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Where You Go is Who You Are: Behavioral Theory-Guided LLMs for Inverse Reinforcement Learning
SILIC uses LLM-guided inverse reinforcement learning and Theory of Planned Behavior chain reasoning to infer age, gender, income, and employment from travel trajectories, reportedly beating SVM, XGBoost, CatBoost, and GPT-4o baselines.