2 papers
cs.AI2026
GT-HarmBench: Benchmarking AI Safety Risks Through the Lens of Game Theory
Pepijn Cobben, Xuanqiang Angelo Huang, Thao Amelia Pham +3
Frontier AI systems are increasingly capable and deployed in high-stakes multi-agent environments. However, existing AI safety benchmarks largely evaluate single agents, leaving mu…
q-fin.PM2024
Double Descent in Portfolio Optimization: Dance between Theoretical Sharpe Ratio and Estimation Accuracy
Yonghe Lu, Yanrong Yang, Terry Zhang
We study the relationship between model complexity and out-of-sample performance in the context of mean-variance portfolio optimization. Representing model complexity by the number…