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      "statement": "# Guo et al.: DeepSeek-Coder project-level code research resource\n\nTrained and released code models on deduplicated project-level repositories with dependency-aware code organization and fill-in-the-middle training, documenting a reusable code-generation and infilling pipeline.\n\n## Scientific scope\n\nProject-level processing and infilling have predecessors; not invention of transformers or all code completion. Original models appeared in2023 and this report is2024. V2 continues an existing MoE/GRPO pipeline and is not a separate acquisition merely for more tokens, languages or context.\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\nDaya Guo; Qihao Zhu; Dejian Yang; Zhenda Xie; Kai Dong; Wentao Zhang; Guanting Chen; Xiao Bi; Y. Wu; Y. K. Li; Fuli Luo; Yingfei Xiong; Wenfeng Liang\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- [DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence](https://arxiv.org/abs/2401.14196v1)\n- [Guo et al.: DeepSeek-Coder project-level code research resource — author/institution implementation](https://github.com/deepseek-ai/DeepSeek-Coder)\n",
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