Toward Personalizable AI Node Graph Creative Writing Support: Insights on Preferences for Generative AI Features and Information Presentation Across Story Writing Processes
Hua Xuan Qin, Guangzhi Zhu, Mingming Fan, Pan Hui
摘要
As story writing requires diverse resources, a single system combining these resources could improve personalization. We leverage the broad capabilities of generative AI to support both more general story writing needs and an understudied but essential aspect: reflection on the moral (lesson) conveyed. Through a formative study (N=12), a user study (N=14), and external evaluation (N=19), we designed, implemented, then studied a prototype plugin for FigJam supporting visualization of the story structure through customizable node graph editing, LLM audience impersonation (chatbot and non-chatbot interfaces), and image and audio generative AI features. Our findings support writers' preference for leveraging unique interplays of our breadth of features to satisfy shifting needs across writing processes, from conveying a moral across audience groups to story writing in general. We discuss how our tool design and findings can inform model bias, personalized writing support, and visualization research.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了最后一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper4
- How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of ScreenwritersYuying Tang, Jiayi Zhou, Haotian Li, Xing Xie 等CHI 2026 · 被引用 6 次
- Plotania: Exploring Transparency Trade-offs in AI Co-Writing Through Virtual Readers and Transparent AttributionYufeng Hu, Jinyi Zhang, Zehuan Wang, Chun YuCHI 2026 · 被引用 1 次
- Vidmento: Creating Video Stories through Context-Aware Expansion with Generative VideoCatherine Yeh, Anh Truong, Mira Dontcheva, Bryan WangCHI 2026 · 被引用 1 次
- CRAFT: Exploring Wearable Creative AI on Smart Glasses for Fiction Writing in Real-World ContextsRunze Cai, Yuxuan Huang, Lin-Ping Yuan, Kexin Xiang 等UbiComp 2026
它引用的顶会 Paper27
- Evaluating the Moral Beliefs Encoded in LLMsNino Scherrer, Claudia Shi, Amir Feder, David M. BleiNeurIPS 2023 · 被引用 316 次
- Can Large Language Models Be an Alternative to Human Evaluations?David Cheng-Han Chiang, Hung-yi LeeACL 2023 · 被引用 254 次
- How WEIRD is CHI?Sebastian Linxen, Christian Sturm, Florian Brühlmann, Vincent Cassau 等CHI 2021 · 被引用 254 次
- Co-Writing Screenplays and Theatre Scripts with Language Models: Evaluation by Industry ProfessionalsPiotr Mirowski, Kory W. Mathewson, Jaylen Pittman, Richard EvansCHI 2023 · 被引用 235 次
- TaleBrush: Sketching Stories with Generative Pretrained Language ModelsJohn Joon Young Chung, Wooseok Kim, Kang Min Yoo, Hwaran Lee 等CHI 2022 · 被引用 202 次
相关 Paper
- Exploring Creator-Centric Methods for LLM-Assisted Interactive StorytellingYuelu Li, Siyi Wu, Lujin Zhang, Zhihan Guo 等CHI 2026 · 被引用 1 次
- Co-Constructed or Constrained? How AI Collaboration Tools Reshape UI Design Practice in a Time-Boxed Design ChallengeCharlotte Kobiella, Lukas Schneider, Albrecht Schmidt, Nada TerzimehicCHI 2026 · 被引用 1 次
- VISAR: A Human-AI Argumentative Writing Assistant with Visual Programming and Rapid Draft PrototypingZheng Zhang, Jie Gao, Ranjodh Singh Dhaliwal, Toby Jia-Jun LiUIST 2023 · 被引用 101 次
- CharacterMeet: Supporting Creative Writers' Entire Story Character Construction Processes Through Conversation with LLM-Powered Chatbot AvatarsHua Xuan Qin, Shan Jin, Ze Gao, Mingming Fan 等CHI 2024 · 被引用 79 次
- Writer-Defined AI Personas for On-Demand Feedback GenerationKarim Benharrak, Tim Zindulka, Florian Lehmann, Hendrik Heuer 等CHI 2024 · 被引用 62 次
