1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.CL2026
DepthCharge: A Domain-Agnostic Framework for Measuring Depth-Dependent Knowledge in Large Language Models
Alexander Sheppert
Large Language Models appear competent when answering general questions but often fail when pushed into domain-specific details. No existing methodology provides an out-of-the-box…
q-fin.ST2026★ 1 cited
The GT-Score: A Robust Objective Function for Reducing Overfitting in Data-Driven Trading Strategies
Alexander Sheppert
Overfitting remains a critical challenge in data-driven financial modeling, where machine learning (ML) systems learn spurious patterns in historical prices and fail out of sample…