SOURCE-LINKED INTELLIGENCE
Learning from Hard Prompts: Difficulty-aware Advantage Amplification in Dynamic Sampling
Decoupled Clip and Dynamic Sampling Policy Optimization (DAPO) is a prominent variant of Group Relative Policy Optimization (GRPO). DAPO introduces several improvements over GRPO. Among these, Dynamic Sampling contributes the most to DAPO's accuracy gains relative to GRPO. To improve accuracy, Dynamic Sampling enhances training stability by eliminating zero policy gradients from zero advantages. Specifically, it avoids such zero gradients by filtering out prompts where sampled responses are either entirely correct or incorrect. However, our theoretical analysis shows that Dynamic Sampling decr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-28T06:51:31.000Z
First collected: 2026-09-21T08:21:55.975Z. This is not the publication date.