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This work proposes a task-specific pruning pipeline, named Cut-ViT, which first construct gram anchoring matrices from both spatial and semantic perspectives, and performs the subspace decomposition to extract the corresponding subspace bases.
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.
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