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Weak-to-Strong Generalization via Direct On-Policy Distillation

📄 Trending Paper (115⬆️): Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on every new strong model because the target model must generate many rollouts during training. As models scale, post-training itself becomes a bottleneck....

Source: HuggingFace_Papers

What it does

📄 Trending Paper (115⬆️): Reinforcement learning with verifiable rewards (RLVR) is a powerful recipe for improving language-model reasoning, but it is expensive to repeat on every new strong model because the target model must generate many rollouts during training. As models scale, post-training itself becomes a bottleneck....

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Weak-to-Strong Generalization via Direct On-Policy Distillation | ToolAI - StudioCentOS