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LLMs can dramatically improve information extraction from messy, real-world investigative documents, but at a steep cost in processing time.
A consensus-driven multi-LLM pipeline can improve information extraction for missing-person investigations, offering a practical approach to leveraging LLMs in high-stakes scenarios.
LLMs can provide quality assurance for reinforcement learning-based search plans in high-stakes missing-child investigations, improving the reliability of AI-driven decision support.