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Experiments show ElementCheck consistently improves factuality verification across five backbone models while maintaining a favorable accuracy-cost trade-off, and further analyses demonstrate that complexity-aware verification reduces unnecessary re-verification and maintains stability across different backbones.
This survey bridges the existing gap by presenting a comprehensive blueprint for scientific agents' design and introduces a unified taxonomy based on capability envelope and capability maturity, characterizing both the scope of scientific workflow coverage and the reliability of agent behavior under realistic research conditions.
SymDiag is proposed, a neuro-symbolic framework that reframes reasoning verification as structured failure diagnosis and incorporates a Self-Auditor that disentangles TranslationError from ReasoningError via dual symbolic encodings consistency checks, enabling robust diagnosis under partial observability.