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MAWILE is introduced, a developer-facing workbench for auditing judge sensitivity across four surfaces: the judge prompt, judge rubric, target-system input, and target-system output, and it audits binary, ordinal, and pairwise judges without requiring gold labels.
A hybrid LLM-guided Bayesian network structure-learning framework that uses LLMs as bounded semantic guides, and shows that language-derived semantic knowledge can substantially improve scalable probabilistic structure learning when used as bounded guidance within a statistically grounded reasoning pipeline.
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