CRGC models instructions as constraint graphs, identifies bridge constraints, and cuts violations by 39% on three datasets while preserving reasoning performance.
A uto DSL : A utomated D omain-specific L anguage D esign for S tructural R epresentation of P rocedures with C onstraints
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Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models
CRGC models instructions as constraint graphs, identifies bridge constraints, and cuts violations by 39% on three datasets while preserving reasoning performance.