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.

References

It is also unclear whether there would be generalization between checkable tasks and estimation questions without ground truth, and between the different forms of value leakage.

— Value Leakage: An LLM's Answers Are Silently Shaped by Its Own Values  (2607.14345 - Betley et al., 15 Jul 2026) in Conclusion and future work

Several important questions remain open, we discuss some in the Limitations below (Section~\ref{sec:limitations}). The most critical is whether debate's benefits transfer to domains without verifiable ground truth.

— Debate Training Reduces Reward Hacking in RLAIF  (2608.17776 - Kenton et al., 18 Aug 2026) in Section 5, subsection “Conclusion”