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Localization in code repair is often ineffective, with blind resampling outperforming targeted edits despite initial expectations.
Annotator identity can drastically alter benchmark outcomes, yet current leaderboards mask this variability, misleading researchers about model performance.
Skill, not lineage, is the key determinant of success in trusted-monitor ensembles, with implications for how we build and evaluate these systems.