auditing-rlhf-reward-hacking

What problem does it solve?

This Skill audits RLHF, DPO, and RLAIF checkpoints for reward hacking, helping you tell whether a model is truly improving or just gaming the learned reward signal.

Core Features & Use Cases

• Reward-vs-preference divergence: Compares reward-model win-rate against held-out preference win-rate to expose the main reward-hacking signal.
• Multi-probe evaluation: Checks length bias, sycophancy, formatting bias, refusal substitution, persuasion over correctness, and boundary exploitation.
• Promotion gate support: Produces a per-probe verdict table, alignment-tax assessment, and final ship or re-tune recommendation before deployment.

Quick Start

Use this skill to audit an RLHF or DPO model by comparing reward-model and held-out preference results, running the standard probes, and deciding whether the checkpoint is safe to promote.