✨Beyond English: Toward Inclusive and Scalable Multilingual Machine Translation with LLMs

📝 Summary:
LMT introduces new multilingual translation models covering 60 languages, centered on Chinese and English. It uses Strategic Downsampling and Parallel Multilingual Prompting to improve translation quality and cross-lingual transfer, achieving state-of-the-art performance.

🔹 Publication Date: Published on Nov 10

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.07003
• PDF: https://arxiv.org/pdf/2511.07003
• Project Page: https://github.com/NiuTrans/LMT
• Github: https://github.com/NiuTrans/LMT

🔹 Models citing this paper:
• https://huggingface.co/NiuTrans/LMT-60-1.7B
• https://huggingface.co/NiuTrans/LMT-60-0.6B-Base
• https://huggingface.co/NiuTrans/LMT-60-0.6B

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For more data science resources:
✓ https://xn--r1a.website/DataScienceT

#MultilingualTranslation #LLMs #MachineTranslation #NLP #AI

✨Mending the Holes: Mitigating Reward Hacking in Reinforcement Learning for Multilingual Translation

📝 Summary:
LLMs struggle with low-resource language translation due to data scarcity. WALAR, a novel RL method, uses only monolingual text to improve LLM translation by mitigating reward hacking in quality estimation models. This significantly outperforms existing multilingual LLMs.

🔹 Publication Date: Published on Mar 13

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2603.13045
• PDF: https://arxiv.org/pdf/2603.13045
• Github: https://github.com/LeiLiLab/WALAR

🔹 Models citing this paper:
• https://huggingface.co/lyf07/LLaMAX3-8B-Alpaca-WALAR
• https://huggingface.co/lyf07/Translategemma-4B-it-WALAR
• https://huggingface.co/lyf07/Qwen3-8B-WALAR

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For more data science resources:
✓ https://xn--r1a.website/DataScienceT

#ReinforcementLearning #LLM #MultilingualTranslation #NLP #LowResourceLanguages