From the 1 of 7 linked papers with an AI index.
7 papers
Step-Level Preference Learning for Generative Agents in Social Simulations
Wenchang Gao, Pingyue Sheng, Lanlan Qiu +7
The paper presents an interactive interface to collect step‑level human preference data for generative agents, creates a 57K annotation dataset, and shows that training LLMs with t…
SidConArena: An Environment Evaluating Agents in Open-Ended,Positive-Sum Bargaining Game
Yeqi Feng, Yuxin Chen, Tianxing He
Evaluating LLM agents requires dynamic environments that go beyond static reasoning and zero-sum games. Real-world economic interaction is often open-ended and mixed-motive: agents…
VirtualCrime: Evaluating the Criminal Potential and Agentic Behaviors of Large Language Models via Sandbox Simulation
Yilin Tang, Yu Wang, Lanlan Qiu +4
Large language models (LLMs) have shown strong capabilities in multi-step decision-making, and are increasingly integrated into real-world agentic applications. While existing safe…
SimCity: Multi-Agent Urban Development Simulation with Rich Interactions
Yeqi Feng, Yucheng Lu, Hongyu Su +2
Large Language Models (LLMs) open new possibilities for constructing realistic and interpretable macroeconomic simulations. We present SimCity, a multi-agent framework that leverag…
A Visualized Framework for Event Cooperation with Generative Agents
Yuyang Tian, Shunqiang Mao, Wenchang Gao +2
Large Language Models (LLMs) have revolutionized the simulation of agent societies, enabling autonomous planning, memory formation, and social interactions. However, existing frame…
LLMs vs. Chinese Anime Enthusiasts: A Comparative Study on Emotionally Supportive Role-Playing
Lanlan Qiu, Xiao Pu, Yeqi Feng +1
Large Language Models (LLMs) have demonstrated impressive capabilities in role-playing conversations and providing emotional support as separate research directions. However, there…