XTransplant empirically shows that cross-lingual latent transplantation yields mutual benefits for multilingual capability and cultural adaptability in LLMs, especially low-resource ones, while revealing underutilized model potential.
On the multilingual ability of decoder-based pre-trained language mod- els: Finding and controlling language-specific neurons,
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Mix-MoE applies separate LM and MT expert groups in two post-pretraining stages with Fourier-enhanced routing to reduce parameter interference and improve multilingual MT over baselines.
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Exploring Cross-lingual Latent Transplantation: Mutual Opportunities and Open Challenges
XTransplant empirically shows that cross-lingual latent transplantation yields mutual benefits for multilingual capability and cultural adaptability in LLMs, especially low-resource ones, while revealing underutilized model potential.
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Mix-MoE: Improving Multilingual Machine Translation of Large Language Models through Mixed MoEs
Mix-MoE applies separate LM and MT expert groups in two post-pretraining stages with Fourier-enhanced routing to reduce parameter interference and improve multilingual MT over baselines.