2 citations · 3 across the 4 of their papers we have counts for
5 papers
AlignUSER: Human-Aligned LLM Agents via World Models for Recommender System Evaluation
Nicolas Bougie, Gian Maria Marconi, Tony Yip +1
Evaluating recommender systems remains challenging due to the gap between offline metrics and real user behavior, as well as the scarcity of interaction data. Recent work explores…
CitySim: Modeling Urban Behaviors and City Dynamics with Large-Scale LLM-Driven Agent Simulation
Nicolas Bougie, Narimasa Watanabe
Modeling human behavior in urban environments is fundamental for social science, behavioral studies, and urban planning. Prior work often rely on rigid, hand-crafted rules, limitin…
SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation
Nicolas Bougie, Narimasa Watanabe
Recommender systems play a central role in numerous real-life applications, yet evaluating their performance remains a significant challenge due to the gap between offline metrics…
MobileCity: An Efficient Framework for Large-Scale Urban Behavior Simulation
Xiaotong Ye, Nicolas Bougie, Toshihiko Yamasaki +1
Generative agents offer promising capabilities for simulating realistic urban behaviors. However, existing methods oversimplify transportation choices, rely heavily on static agent…
Generative Adversarial Reviews: When LLMs Become the Critic
Nicolas Bougie, Narimasa Watanabe
The peer review process is fundamental to scientific progress, determining which papers meet the quality standards for publication. Yet, the rapid growth of scholarly production an…