Performance gaps in multilingual LMs frequently arise from modeling choices such as tokenization and data exposure rather than intrinsic linguistic complexity.
InFindings of the Association for Computational Linguistics: ACL 2023, Toronto, Canada, July 9-14, 2023, pages 598–614
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The Roots of Performance Disparity in Multilingual Language Models: Intrinsic Modeling Difficulty or Design Choices?
Performance gaps in multilingual LMs frequently arise from modeling choices such as tokenization and data exposure rather than intrinsic linguistic complexity.