AI RESEARCH
Real-Time Trustworthiness Scoring for LLM Structured Outputs and Data Extraction
arXiv CS.LG
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ArXi:2603.18014v1 Announce Type: cross Structured Outputs from current LLMs exhibit sporadic errors, hindering enterprise AI efforts from realizing their immense potential. We present CONSTRUCT, a method to score the trustworthiness of LLM Structured Outputs in real-time, such that lower-scoring outputs are likely to contain errors. This reveals the best places to focus limited human review bandwidth. CONSTRUCT additionally scores the trustworthiness of each field within a LLM Structured Output, helping reviewers quickly identify which parts of the output are wrong.