Author

Linjian Meng

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#artificial intelligence Preprint Aug 2026

Learning from Hard Prompts: Difficulty-aware Advantage Amplification in Dynamic Sampling

Direct Advantage Amplification (DAA), which amplifies the advantages of hard-to-sample correct responses on hard prompts, as obtained by Dynamic Sampling, is proposed, which ensures that, when Dynamic Sampling is used, these hard-to-sample responses can be effectively capitalized on, implying higher training efficiency.

Si-Yuan Gan, Yu-Hang Li, Xiran Wang et al. · 0 citations

#artificial intelligence Preprint Aug 2026

When Teacher Guidance Misleads: Reward-Aligned On-Policy Distillation

RA-OPD selects more reliable trajectories to improve student model performance without requiring additional computational cost and is evaluated on math and code benchmarks using models from the Qwen3 family and the DeepSeek-R1 family.

Si-Yuan Gan, Yu-Hang Li, Xiran Wang et al. · 0 citations