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LoRA fine-tuning yields higher sentence extraction accuracy and higher point estimates on all three reference-based correction similarity metrics in both languages, and several leading general-purpose reasoning models outperform all three evaluated medical-domain models on these two subtasks.
PDC consistently improves upon the initial sample, outperforms independent generations under a computational constrained comparison, and is robust to different unmasking strategies and parameter settings, highlighting prefix-conditioned regeneration as an effective DLM-specific primitive for test-time verification.
The role of target-specific privilege is investigated with On-Policy Self-Distillation from Other Problems (On-Policy Self-Distillation from Other Problems), which replaces the paired reference with a problem and solution from a different example, while preserving the student rollout, teacher, and distillation objectiv...
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