EMNLP 2026 paper examines how training data shapes AI word order preferences
One of its authors frames the research as a way to uncover language models’ implicit biases and better understand risks to the diversity of language structures worldwide.
TLDR
An author announced an EMNLP 2026 paper exploring how training data shapes language models’ word order preferences. They connect the work on implicit biases to a broader concern: the risks that adopting large language models could pose to the diversity of language structures worldwide.
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