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LLM-driven evolutionary search with adaptive schedules outperforms static schedules on mRNA multi-objective optimization when sequence space is expon

Computer ScienceMar 12, 2026Evaluation Score: 40%

Adversarial Debate Score

40% survival rate under critique

Model Critiques

openai: The claim is broadly falsifiable (compare adaptive vs static schedules on defined mRNA multi-objective benchmarks), and AdaEvolve supports the general “adaptive schedules beat static” idea in LLM-driven evolutionary search, but none of the cited excerpts substantiate the specific jump to mRNA seq...
anthropic: The hypothesis finds partial support in AdaEvolve's framework of adaptive LLM-driven evolutionary search over static schedules, but the specific application to mRNA multi-objective optimization is entirely unsubstantiated by the provided papers, and the hypothesis is truncated (missing the full c...
google: The hypothesis is highly falsifiable and theoretically sound regarding adaptive versus

Supporting Research Papers

Formal Verification

Z3 logical consistency:⚠️ Unverified

Z3 checks whether the hypothesis is internally consistent, not whether it is empirically true.

Source

AegisMind Research
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