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cs.LG2026
Eliciting Weak-to-Strong Generalization with On-Policy Reverse Distillation
Youngrok Park, Sangmin Bae, Hojung Jung +6
Weak-to-strong generalization asks whether stronger models can learn from weaker supervisors and surpass them. This is particularly important for successive model generations and m…
cs.LG2026
Scaling Reasoning Efficiently via Relaxed On-Policy Distillation
Jongwoo Ko, Sara Abdali, Young Jin Kim +2
On-policy distillation (OPD) is a promising approach for transferring reasoning capabilities to capacity-constrained models, yet sampled-token OPD often suffers from entropy collap…