: This paper investigates whether multilingual models learn syntax that corresponds to typological features found in WALS.
While a single "complete paper" with this exact title does not exist in public journals, the file corresponds to the experimental setup for a series of influential papers exploring how transformer models (like RoBERTa) encode linguistic features. 1. The Context of the Research WALS_Roberta Sets 182-184 195.rar
If you are looking for the specific paper that originally distributed this exact rar file, it is most likely a or a Zenodo/Open Science Framework (OSF) supplement for a thesis or a conference paper from the ACL (Association for Computational Linguistics) . : This paper investigates whether multilingual models learn
: Often associated with Lexical Categories or specific Inflectional Paradigms . How to Find the Full Document The Context of the Research If you are
: A large database of structural properties (phonological, grammatical, lexical) of languages.
The "Sets" mentioned (182-184, 195) typically refer to specific . The most relevant research examining these specific intersections includes:
: This line of research uses WALS features as a benchmark to test if models can predict the linguistic category of a language based only on its internal representations.