Chinese BabyLM Cog A197 Strict Best Model Summary chinese babylm cog a197 strict best is a custom BERT based wrapper model for the NLPCC 2026 Chinese BabyLM shared task, optimized for the Cognitive Modeling (Cog) Track . It combines internal strict BERT branches, official corpus static features, and MLM uncertainty features for brain aligned fMRI evaluation. Competition Compliance Requirement Status From scratch Source weights from internal random initialized strict lineage only No pretrained checkpoint No official baseline or external pretrained checkpoint No distillation No teacher model distillation Data option Official corpus ( chinese babylm org/babylm zho 100M ) Evaluation leakage No CogBench stimulus text, labels, predictions, or item level feedback used in training No external resources No pypinyin, IDS/CJKVI, radical tables, glyph/font resources, or inference time rules Frozen submission Single exported wrapper checkpoint Architecture Field Value Model type CogAllLayerUncertaintyGate wrapper Architecture CogAllLayerUncertaintyGateModel Backend mlm Hidden size 1409 Max positions 256 Vocabulary 16000 (WordPiece, trained on official corpus) Components Word branch: A180 strict…
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