COIG-Writer：一个包含思维过程的高质量中文创意写作数据集

COIG-Writer: A High-Quality Dataset for Chinese Creative Writing with Thought Processes

October 16, 2025

作者: Yunwen Li, Shuangshuang Ying, Xingwei Qu, Xin Li, Sheng Jin, Minghao Liu, Zhoufutu Wen, Tianyu Zheng, Xeron Du, Qiguang Chen, Jiajun Shi, Wangchunshu Zhou, Jiazhan Feng, Wanjun Zhong, Libo Qin, Stephen Huang, Wanxiang Che, Chenghua Lin, Eli Zhang

cs.AI

摘要

大型語言模型在創意寫作方面表現出系統性缺陷，尤其是在非英語語境中，訓練數據稀缺且缺乏過程層面的監督。我們提出了COIG-Writer，這是一個新穎的中文創意寫作數據集，通過對高質量文本進行系統逆向工程，捕捉了多樣化的輸出及其背後的思維過程。與現有僅提供輸入-輸出對的數據集不同，COIG-Writer包含1,665個精心策劃的三元組，涵蓋51種文體，每個三元組包含：(1) 逆向工程生成的提示，(2) 詳細記錄決策過程的創意推理，以及(3) 最終文本。通過全面實驗，我們識別出創意寫作的雙組分模型：敘事邏輯（由過程監督提供）和語言表達（由通用數據維持）。我們的研究揭示了三個關鍵見解：(1) 過程監督極為有效，但需要與通用數據結合以穩定效果。達到最佳性能需至少一個創意樣本對應十二個通用樣本；低於此閾值，勝率逐漸下降（從62.75%降至35.78%）。(2) 創意能力具有文化依賴性，不存在跨語言遷移（中文與英文表現之間存在89.26個百分點的差距）。(3) 詞彙多樣性與創意質量呈負相關（TTR悖論），表明高多樣性暗示了對邏輯缺陷的補償行為。這些發現確立了創意卓越源於邏輯框架與語言基礎的相互作用，類似於數學推理在基礎模型中增強但無法替代語言能力的情形。

English

Large language models exhibit systematic deficiencies in creative writing, particularly in non-English contexts where training data is scarce and lacks process-level supervision. We present COIG-Writer, a novel Chinese creative writing dataset that captures both diverse outputs and their underlying thought processes through systematic reverse-engineering of high-quality texts. Unlike existing datasets that provide only input-output pairs, COIG-Writer comprises 1,665 meticulously curated triplets spanning 51 genres, each containing: (1) a reverse-engineered prompt, (2) detailed creative reasoning documenting decision-making processes, and (3) the final text. Through comprehensive experiments, we identify a two-component model of creative writing: narrative logic (provided by process supervision) and linguistic expression (maintained by general-purpose data). Our findings reveal three critical insights: (1) Process supervision is highly effective but requires stabilization with general data. A ratio of at least one creative sample to twelve general samples is needed to achieve optimal performance; below this threshold, the win rate progressively degrades (from 62.75% down to 35.78%)., (2) creative capabilities are culturally-bound with no cross-lingual transfer (89.26pp gap between Chinese and English performance), and (3) lexical diversity inversely correlates with creative quality (TTR paradox), suggesting high diversity signals compensatory behavior for logical deficiencies. These findings establish that creative excellence emerges from the interaction between logical scaffolding and linguistic grounding, analogous to how mathematical reasoning enhances but cannot replace linguistic competence in foundation models.