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      "statement": "# Kim et al.: pretrained-layer depth up-scaling\n\nCopied a pretrained transformer, removed complementary top/bottom layer blocks and concatenated retained layers before continued training, increasing depth while reducing discontinuity at the join.\n\n## Scientific scope\n\nLayer reuse, model growth and continued pretraining have predecessors. Source uses Llama2 architecture initialized with Mistral7B weights; not a new backbone trained from scratch or MoE. A particular48-layer construction does not prove optimality or compatibility with all transformer implementations.\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\nDahyun Kim; Chanjun Park; Sanghoon Kim; Wonsung Lee; Wonho Song; Yunsu Kim; Hyeonwoo Kim; Yungi Kim; Hyeonju Lee; Jihoo Kim; Changbae Ahn; Seonghoon Yang; Sukyung Lee; Hyunbyung Park; Gyoungjin Gim; Mikyoung Cha; Hwalsuk Lee; Sunghun Kim\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling](https://arxiv.org/abs/2312.15166v1)\n- [Kim et al.: pretrained-layer depth up-scaling — author/institutional project](https://huggingface.co/upstage/SOLAR-10.7B-v1.0)\n",
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