7 papers
MASLab: A Unified and Comprehensive Codebase for LLM-based Multi-Agent Systems
Rui Ye, Keduan Huang, Qimin Wu +17
LLM-based multi-agent systems (MAS) have demonstrated significant potential in enhancing single LLMs to address complex and diverse tasks in practical applications. Despite conside…
DEpiABS: Differentiable Epidemic Agent-Based Simulator
Zhijian Gao, Shuxin Li, Bo An
The COVID-19 pandemic highlighted the limitations of existing epidemic simulation tools. These tools provide information that guides non-pharmaceutical interventions (NPIs), yet ma…
Bayesian Robust Financial Trading with Adversarial Synthetic Market Data
Haochong Xia, Simin Li, Ruixiao Xu +7
Algorithmic trading relies on machine learning models to make trading decisions. Despite strong in-sample performance, these models often degrade when confronted with evolving real…
C2PO: Diagnosing and Disentangling Bias Shortcuts in LLMs
Xuan Feng, Bo An, Tianlong Gu +4
Bias in Large Language Models (LLMs) poses significant risks to trustworthiness, manifesting primarily as stereotypical biases (e.g., gender or racial stereotypes) and structural b…
MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework
Qirui Mi, Mengyue Yang, Xiangning Yu +6
Simulating collective decision-making involves more than aggregating individual behaviors; it emerges from dynamic interactions among individuals. While large language models (LLMs…
EconGym: A Scalable AI Testbed with Diverse Economic Tasks
Qirui Mi, Qipeng Yang, Zijun Fan +7
Artificial intelligence (AI) has become a powerful tool for economic research, enabling large-scale simulation and policy optimization. However, applying AI effectively requires si…