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New distillation technique boosts multilingual math reasoning in LLMs

By PulseAugur Editorial · [1 sources] ·

Researchers have explored On-Policy Delta Distillation (OPD^2), an advancement over On-Policy Distillation (OPD), for multilingual mathematical reasoning. Experiments using the Qwen3 model demonstrated that OPD^2 significantly outperforms standard OPD across English, Korean, and Japanese. The study also noted that while English-only OPD can boost performance in other languages, it may inadvertently shift responses towards English, underscoring the need for multilingual data to maintain language-specific responses. AI

IMPACT This research could lead to more effective multilingual LLMs for complex reasoning tasks.

RANK_REASON The cluster contains a research paper detailing a new technique for LLM post-training. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New distillation technique boosts multilingual math reasoning in LLMs

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The cluster contains a research paper detailing a new technique for LLM post-training. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    On-Policy Delta Distillation for Multilingual Math Reasoning

    On-Policy Distillation (OPD) is emerging as a promising alternative to reinforcement learning for LLM post-training, yet its effectiveness in multilingual settings remains underexplored. We study OPD and its advanced variant, On-Policy Delta Distillation (OPD$^2$), for mathematic…

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