5 papers
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…
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…
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…
From Understanding to Excelling: Template-Free Algorithm Design through Structural-Functional Co-Evolution
Zhe Zhao, Haibin Wen, Pengkun Wang +8
Large language models (LLMs) have greatly accelerated the automation of algorithm generation and optimization. However, current methods such as EoH and FunSearch mainly rely on pre…