9 citations · 12 across the 9 of their papers we have counts for
9 papers
CityReal: Human-Aligned Urban Behavior and City Dynamics Simulation with Large-Scale LLM Agents
Nicolas Bougie, Xiaotong Ye, Narimasa Watanabe
Large-scale urban simulation plays a pivotal role in social science, traffic safety, and transportation policy. Recent work has shown that large language models, when prompted as a…
PerceptUI: LLM Agents as Human-Aligned Synthetic Users for UI/UX Evaluation
Nicolas Bougie, Xiaotong Ye, Gian Maria Marconi +1
User interface (UI) and user experience (UX) evaluation is central to product development, yet reliable feedback still relies on recruiting human participants or running online A/B…
Beyond Offline A/B Testing: Context-Aware Agent Simulation for Recommender System Evaluation
Nicolas Bougie, Gian Maria Marconi, Xiaotong Ye +1
Recommender systems are central to online services, enabling users to navigate through massive amounts of content across various domains. However, their evaluation remains challeng…
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…
Deep Reinforcement Learning Boosted by External Knowledge
Nicolas Bougie, Ryutaro Ichise
Recent improvements in deep reinforcement learning have allowed to solve problems in many 2D domains such as Atari games. However, in complex 3D environments, numerous learning epi…