Pairwise AI Ranking (PAIR): open parse evaluation

Reducto introduces Pairwise AI Ranking (PAIR), an open evaluation framework for document parsers that uses an LLM judge to compare two blinded parses against an original page image and determine which more faithfully preserves information. The company argues that conventional rule-based and ground-truth benchmarks can be brittle because they often penalize harmless differences in markup or formatting while missing consequential errors such as incorrect table relationships, values, reading order, or key-value pairings. PAIR compares each candidate parser with a shared baseline across benchmark pages, repeats judgments three times with shuffled output order, and calculates win rates with ties counted as half wins. In a third-party annotation study of 300 comparisons, the LLM judge agreed with final human decisions 84.0% of the time when both selected a winner and 91.6% when human reviewers were unanimous. Controlled edits also found that the judge consistently treated formatting-only changes as ties while detecting meaningful content changes, such as altered digits or swapped table cells and paragraphs, at high rates. Reducto has published the judge prompt and ParseJudge tool so organizations can evaluate parsers on their own documents without creating document-specific rules or extensive human-labeled datasets.

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