CRGC models instructions as constraint graphs, identifies bridge constraints, and cuts violations by 39% on three datasets while preserving reasoning performance.
L earning A ction C onditions from I nstructional M anuals for I nstruction U nderstanding
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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.