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      "statement": "# Lan and colleagues: ALBERT parameter-efficient language representations\n\nReduced BERT-style model parameters through factorized embeddings and cross-layer sharing while evaluating language-understanding performance.\n\n## Scientific scope\n\nFirst preprint appeared in 2019; year follows ICLR 2020. ALBERT is a BERT-derived design, not original bidirectional pre-training.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nZhenzhong Lan; Mingda Chen; Sebastian Goodman; Kevin Gimpel; Piyush Sharma; Radu Soricut\n\nComplete named paper byline. Human research, source-reported system execution and experimental validation are distinct; individual effort shares are not measured.\n\n\n\n## Original sources\n\n- [Lan and colleagues: ALBERT parameter-efficient language representations — original paper](https://arxiv.org/abs/1909.11942v6)\n- [Lan and colleagues: ALBERT parameter-efficient language representations — official company source](https://research.google/blog/albert-a-lite-bert-for-self-supervised-learning-of-language-representations/)\n",
      "summary": "Reduced BERT-style model parameters through factorized embeddings and cross-layer sharing while evaluating language-understanding performance.",
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