Low-resource languages are structurally more different from English in LLMs than high- or mid-resource ones, and language-specific post-training alters structures while preserving inter-language relationships.
InProceedings of the 1st Workshop on Multilingual Representation Learning, Duygu Ataman, Alexandra Birch, Alexis Conneau, Orhan Firat, Sebastian Ruder, and Gozde Gul Sahin (Eds.)
2 Pith papers cite this work, alongside 15 external citations. Polarity classification is still indexing.
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Model developers must address human concerns, preferences, values, and goals with rigor at every stage of the LLM pipeline rather than only in post-training.
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Multilinguality of Large Language Models From a Structural Perspective
Low-resource languages are structurally more different from English in LLMs than high- or mid-resource ones, and language-specific post-training alters structures while preserving inter-language relationships.
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Reflections and New Directions for Human-Centered Large Language Models
Model developers must address human concerns, preferences, values, and goals with rigor at every stage of the LLM pipeline rather than only in post-training.