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Counterfactual Constraint-Conditioned On-Policy Distillation for Multi-Constraint Instruction Following

arXiv · AI, language, vision and robotics · article · Sep 23, 2026 · UTC

Multi-constraint instruction following requires a model to respond to a query under many simultaneously active constraints. Even strong instruction-tuned models still routinely violate some of them. Existing approaches either augment supervision with sequence- or token-level RL rewards from external verifiers or learned graders, or use on-policy distillation (OPD) against a single full-context teacher whose probability mass becomes diluted as more constraints become simultaneously active. We propose CC-OPD (Counterfactual Constraint-Conditioned On-Policy Distillation), which inverts the standa

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