DuDi: Dual-Signal Distillation with Cross-Lingual Verbalizer
Small language models (SLMs) are efficient and scalable, but their multilingual capabilities degrade severely at sub-billion scales, especially for Southeast Asian (SEA) languages. We introduce DuDi, a dual-signal multilingual distillation framework that combines an online sequence-level signal with off-policy and on-policy token-level signals. DuDi further uses a cross-lingual verbalizer to refine teacher feedback and improve teacher-student transferability in multilingual settings. Experiments on SEA-HELM across multiple model families, scales, and teacher-student settings show that DuDi consistently outperforms competitive distillation baselines. Ablations and analyses confirm that seq...
| Authors | Patomporn Payoungkhamdee, Tinnakit Udsa, Jian Gang Ngui et al. |
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| Primary category | cs.CL |
| Published | 3 June 2026 |
| Last updated at source | 10 June 2026 |
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