arXivPaperNeeds Review

RP-OPSD: Reasoning-Pivot-Guided On-Policy Self-Distillation for Multilingual Reasoning Transfer

RP-OPSD targets cross-lingual distillation at tokens that steer reasoning rather than surface wording, a useful training pattern for multilingual reasoning models.

arXiv

Open Source Open Markdown Open JSON

Source Summary

**RP-OPSD** identifies reasoning pivots by comparing matched teacher views with and without an English reference solution. It was evaluated on mathematical reasoning benchmarks spanning **17 languages** and multiple difficulty levels.

Practical Implication

If training multilingual reasoning models, consider weighting supervision toward reasoning-control decisions and state updates instead of treating every generated token equally. The method also uses reference anchoring around those pivots.

Agent-Ready Context

**RP-OPSD** identifies reasoning pivots by comparing matched teacher views with and without an English reference solution. It was evaluated on mathematical reasoning benchmarks spanning **17 languages** and multiple difficulty levels.

If training multilingual reasoning models, consider weighting supervision toward reasoning-control decisions and state updates instead of treating every generated token equally. The method also uses reference anchoring around those pivots.

The material reports gains over multilingual baselines and OPSD variants but provides no scores or model-level breakdowns. Evidence is limited to mathematical reasoning, so transfer to coding agents is still open.

Context Map

model#reasoning

Uncertainty

The material reports gains over multilingual baselines and OPSD variants but provides no scores or model-level breakdowns. Evidence is limited to mathematical reasoning, so transfer to coding agents is still open.