Input/output constraints boost LLM-generated decision model structural similarity to gold standards by 37-54%, with models matching gold outcomes on 51-53% of test scenarios while removing redundant logic.
ACM29, 5 (May 1986), 370–386
2 Pith papers cite this work. Polarity classification is still indexing.
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Rulemapping uses expert symbolic scaffolds to constrain LLMs, raising precision on §130(1) German hate-speech classification from 0.34-0.49 to 0.80-0.86 while preserving recall of 0.82-0.89.
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From Legal Text to Executable Decision Models: Evaluating Structured Representations for Legal Decision Model Generation
Input/output constraints boost LLM-generated decision model structural similarity to gold standards by 37-54%, with models matching gold outcomes on 51-53% of test scenarios while removing redundant logic.
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Beyond Imperfect Alternatives with Rulemapping: A Neuro-Symbolic Case Study on Online Hate Speech
Rulemapping uses expert symbolic scaffolds to constrain LLMs, raising precision on §130(1) German hate-speech classification from 0.34-0.49 to 0.80-0.86 while preserving recall of 0.82-0.89.