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Born Speaking French (BabyLM 2026)

Right Tool, Right Job: Why Training Language Matters More Than Training Data. Code, data pipeline, and paper sources for the BabyLM 2026 submission on French morphological efficiency at child scale.

About. This work tests, at child-scale data budgets, whether the structure of the training language drives grammar acquisition more than the volume of data does, a direct probe of the Language-Only Hypothesis. By Adam Zachary Wasserman (ORCID, OSF) and David Beauchemin (Université Laval), part of the research program of the Open Honest Foundation. See also fractal-language.

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Born Speaking French: BabyLM 2026 submission — French morphological efficiency at child-scale

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