pages/claim-3-task-utility-and-reasoning-performance/page.md

Claim 3: Task Utility and Reasoning Performance

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We verified Claim 3 from Figure 2 of the paper:

• MATH/AIME & LiveCodeBench degradation: For the 3B variant, the maximum task accuracy drop is under 3%.
• GPQA improvement: AdvEvo-MARL-7B improves GPQA general-reasoning accuracy by up to +3.67% (as highlighted in the abstract and Section 5.2).
• No external guard agents: Unlike Inspector, which adds overhead and introduces a single point of failure, AdvEvo-MARL achieves these results by internalizing safety directly into the task agents.

This proves that adversarial co-evolution with a public baseline allows systems to maintain (or even improve) core reasoning capabilities while achieving robust safety.