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DescGuard is proposed, a registration-time defense that restores the targeted planning metrics and downstream performance toward their baseline levels without modifying worker implementations, the planner, or the orchestration logic, and composes with existing isolation, permission-control, and runtime mechanisms.
LLMs can be made more accurate *and* more trustworthy with a clever post-training method that selectively amplifies only the reasoning steps that progressively build confidence in the correct answer.
