Papers
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Online Shopping Behavior Modeling
PAARS: Persona Aligned Agentic Retail Shoppers
Published:3/31/2025
LLM-based Recommendation SystemsOnline Shopping Behavior ModelingPersona Generation and ApplicationAgent Behavior SimulationConsumer Behavior Distribution Alignment
PAARS framework creates personadriven retail agents equipped with shopping tools and aligns their grouplevel behavior distributions with humans, improving simulation accuracy and enabling automated A/B testing applications.
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Customer-R1: Personalized Simulation of Human Behaviors via RL-based LLM
Agent in Online Shopping
Published:10/9/2025
RL Training for Large Language ModelsLLM-guided motion planningPersonalized User Behavior SimulationOnline Shopping Behavior ModelingReward-Based Action Generation
CustomerR1 uses RLbased LLMs conditioned on user personas for personalized stepwise behavior simulation in online shopping, outperforming prompting and supervised finetuning in accuracy and fidelity on the OPeRA dataset.
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Shop-R1: Rewarding LLMs to Simulate Human Behavior in Online Shopping
via Reinforcement Learning
Published:7/24/2025
RL Training for Large Language ModelsLLM Reasoning Capacity EnhancementLLM-guided motion planningHuman Behavior SimulationOnline Shopping Behavior Modeling
ShopR1 uses reinforcement learning with distinct rewards for rationale generation and action prediction to enhance LLMs' simulation of online shopping behavior, achieving over 65% performance improvement over baselines.
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