More Correct Mass, Worse Answers: Why Power Sampling Can Fail and How to Fix It

TL;DR - Power Sampling can increase probability mass on correct reasoning trajectories yet reduce downstream accuracy by narrowing useful path coverage. A deformation-controlled, support-preserving alternative avoids this failure and improves multi-sample reasoning inference.

• Standard Power Sampling caused self-consistency accuracy drops of up to 18.5 percentage points.
• Fixed exponents create a “dose mismatch,” changing distributions unevenly across problems.
• Global sharpening creates a “coverage mismatch,” suppressing moderate-probability reasoning paths despite high pass@k.
• Weighted self-consistency with the repaired sampler reversed these losses under the same inference budget.