Generalization of mitigation methods across task types and leakage forms

Ascertain whether training approaches that reduce bias on checkable tasks with ground-truth answers generalize to estimation questions without ground truth and across different forms of value leakage.

Background

The paper discusses potential mitigation strategies for covert value leakage but notes that some tasks lack ground-truth labels, complicating reward design for unbiasedness and raising doubts about the breadth of generalization.

Clarifying cross-task generalization is important for building training procedures that robustly reduce value leakage beyond narrowly checkable settings and across qualitatively different leakage mechanisms.