On the Interplay between Positional Encodings, Morphological Complexity, and Word Order Flexibility

The study published on arXiv examines the interplay between positional encodings, morphological complexity, and word order flexibility, a topic of growing interest in the field of language modeling. By pretraining monolingual models with different positional encodings across seven typologically diverse languages, the researchers aimed to test the trade-off hypothesis, which suggests that more morphologically complex languages can exhibit more flexible word orders. However, contrary to earlier findings, the study revealed no clear interaction between positional encodings and these linguistic features. This outcome emphasizes the need for careful consideration of the choice of tasks, languages, and metrics when drawing conclusions in language modeling research. As language model architectures are primarily designed for English, understanding their performance across structurally different languages is crucial for advancing AI language processing capabilities.