RP-OPSD: Reasoning-Pivot-Guided On-Policy Self-Distillation for Multilingual Reasoning Transfer
Score
72提出推理支点这一新视角，并用分布偏移实现无监督识别，增量明显。
方法描述清晰，实验覆盖多语言多难度，分析深入，质量高。
开源代码，可直接应用于多语言推理模型训练，实用性强。
当前多语言推理研究热度高，方法具有实时参考价值。
来自 arXiv，作者单位为 NJUNLP，论文完整且含实验代码，可信度较高。
Base 80.5 × T2 Source weight ×0.9 = 72
Curation line 70Selected
Why selected
The method is novel with thorough experiments and open-sourced code, offering strong reference value for multilingual reasoning research.
AI commentary
「Multilingual reasoning transfer has long been constrained by undifferentiated supervision signals. RP-OPSD cleverly uses teacher-view distribution shifts to automatically locate reasoning pivots. For researchers working on multilingual LLM training or distillation, this paper offers a simple and reproducible improvement strategy worth reading.」
Quick overview
RP-OPSD proposes a self-distillation method for multilingual reasoning transfer. On-policy self-distillation (OPSD) provides dense token-level supervision but does not explicitly prioritize the reasoning signals that matter most for cross-lingual transfer. The method decomposes target-language reasoning into surface text and reasoning pivots, and uses the distributional shift between matched teacher views with and without an English reference solution as a proxy for pivots, enabling privileged distillation and reference anchoring. Experiments on mathematical reasoning benchmarks spanning 17 languages and multiple difficulty levels show that RP-OPSD outperforms strong multilingual reasoning baselines and OPSD variants. Analysis shows it concentrates privileged distillation on reasoning-control and problem-conditioned state-update tokens, downweighting surface realization tokens. Code is open-sourced.
- Introduces reasoning pivots as key supervision signals for cross-lingual transfer, defined as tokens that advance or redirect reasoning.
- Locates reasoning pivots unsupervised via distributional shift between teacher views with and without English reference solutions.
- Outperforms OPSD and strong baselines on mathematical reasoning benchmarks across 17 languages.
- Open-sources code for easy reproduction and extension.
Full text
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