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Weaver: Foundation Models for Creative Writing

Paper · 2024 · Tiannan Wang; Jiamin Chen; Qingrui Jia; Shuai Wang; Ruoyu Fang; Huilin Wang; Zhaowei Gao; Chunzhao Xie; Chuou Xu; Jihong Dai; Yibin Liu; Jialong Wu; Shengwei Ding; Long Li; Zhiwei Huang; Xinle Deng; Teng Yu; Gangan Ma; Han Xiao; Zixin Chen; Danjun Xiang; Yunxia Wang; Yuanyuan Zhu; Yi Xiao; Jing Wang; Yiru Wang; Siran Ding; Jiayang Huang; Jiayi Xu; Yilihamu Tayier; Zhenyu Hu; Yuan Gao; Chengfeng Zheng; Yueshu Ye; Yihang Li; Lei Wan; Xinyue Jiang; Yujie Wang; Siyu Cheng; Zhule Song; Xiangru Tang; Xiaohua Xu; Ningyu Zhang; Huajun Chen; Yuchen Eleanor Jiang; and Wangchunshu Zhou

Summary

General-purpose LLMs write fluently, but in creative and professional genres their prose often sounds flat and machine-like. The authors trace this to two causes. Pre-training relies on noisy or AI-generated web text, and alignment data comes from crowdworkers rather than skilled writers.

Weaver, built by AIWaves Inc., is a model family that is continually pre-trained on a filtered corpus made up mostly of books, fiction, stories and articles. It is then aligned using two data-synthesis techniques:

  • Instruction backtranslation generates plausible instructions for existing high-quality human texts, so annotators only need to gather good content.
  • Constitutional DPO builds preference pairs from expert-written positives and synthesized negatives that deliberately break principles set by professional editors.

Training data also covers RAG, function calling, instruction annotation and evaluation of writing.

On WriteBench, a newly released writing benchmark, every Weaver size beats generalist models several times larger. The largest model exceeds GPT-4 in various scenarios. The results suggest that specializing a model for writing is worthwhile. Weaver powers the WawaWriter collaborative writing platform.

Key points

  • Four sizes: Weaver Mini (1.8B), Base (6B), Pro (14B) and Ultra (34B). A routing agent can pick among them by query complexity to trade quality against compute cost.
  • Instruction backtranslation draws on LongForm and Humpback. Constitutional DPO combines ideas from DPO, Constitutional AI, Self-Align and RLCD, and its preference pairs carry less noise than pairs of two model outputs judged by an LLM.
  • WriteBench is presented as the first benchmark of LLM writing ability. Weaver was compared against 10+ generalist LLMs, with Weaver Ultra reaching state of the art on it.
  • A user study with writers found faster work with Weaver, mainly because its more human-like output needed less post-editing.
  • WawaWriter offers several features:
    • writing agents built on the Agents framework that act as co-authors;
    • personal knowledge bases (VectorDB retrieval, GPT-4V captions for images);
    • user-profile-based personalization;
    • unbounded long-text generation via RecurrentGPT-style recurrent prompting.

Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.

 Fields, topics and concepts

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 16,667 worksArtificial Intelligence · 16,194 worksArts and Humanities · 16,039 worksLanguage and Linguistics · 15,891 worksComputer Vision and Pattern Recognition · 2,869 works

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 3,320 works

Cite

Cite as Tiannan Wang; Jiamin Chen; Qingrui Jia; Shuai Wang; Ruoyu Fang; Huilin Wang; Zhaowei Gao; Chunzhao Xie; Chuou Xu; Jihong Dai; Yibin Liu; Jialong Wu; Shengwei Ding; Long Li; Zhiwei Huang; Xinle Deng; Teng Yu; Gangan Ma; Han Xiao; Zixin Chen; Danjun Xiang; Yunxia Wang; Yuanyuan Zhu; Yi Xiao; Jing Wang; Yiru Wang; Siran Ding; Jiayang Huang; Jiayi Xu; Yilihamu Tayier; Zhenyu Hu; Yuan Gao; Chengfeng Zheng; Yueshu Ye; Yihang Li; Lei Wan; Xinyue Jiang; Yujie Wang; Siyu Cheng; Zhule Song; Xiangru Tang; Xiaohua Xu; Ningyu Zhang; Huajun Chen; Yuchen Eleanor Jiang; and Wangchunshu Zhou. 2024. Weaver: Foundation Models for Creative Writing. arXiv:2401.17268.

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.48550/arxiv.2401.17268 · arXiv 2401.17268

@misc{jiang2024weaver,
  title = {{Weaver: Foundation Models for Creative Writing}},
  author = {Tiannan Wang; Jiamin Chen; Qingrui Jia; Shuai Wang; Ruoyu Fang; Huilin Wang; Zhaowei Gao; Chunzhao Xie; Chuou Xu; Jihong Dai; Yibin Liu; Jialong Wu; Shengwei Ding; Long Li; Zhiwei Huang; Xinle Deng; Teng Yu; Gangan Ma; Han Xiao; Zixin Chen; Danjun Xiang; Yunxia Wang; Yuanyuan Zhu; Yi Xiao; Jing Wang; Yiru Wang; Siran Ding; Jiayang Huang; Jiayi Xu; Yilihamu Tayier; Zhenyu Hu; Yuan Gao; Chengfeng Zheng; Yueshu Ye; Yihang Li; Lei Wan; Xinyue Jiang; Yujie Wang; Siyu Cheng; Zhule Song; Xiangru Tang; Xiaohua Xu; Ningyu Zhang; Huajun Chen; Yuchen Eleanor Jiang; and Wangchunshu Zhou},
  year = {2024},
  doi = {10.48550/arxiv.2401.17268},
  eprint = {2401.17268},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.2401.17268}
}

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