Paper ID: 2311.00488

Comparing Optimization Targets for Contrast-Consistent Search

Hugo Fry, Seamus Fallows, Ian Fan, Jamie Wright, Nandi Schoots

We investigate the optimization target of Contrast-Consistent Search (CCS), which aims to recover the internal representations of truth of a large language model. We present a new loss function that we call the Midpoint-Displacement (MD) loss function. We demonstrate that for a certain hyper-parameter value this MD loss function leads to a prober with very similar weights to CCS. We further show that this hyper-parameter is not optimal and that with a better hyper-parameter the MD loss function attains a higher test accuracy than CCS.

Submitted: Nov 1, 2023