Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas
Allen Institute for AI（艾伦人工智能研究所）；The University of Washington（华盛顿大学）；Hebrew University of Jerusalem（耶路撒冷希伯来大学）；Carnegie Mellon University（卡内基梅隆大学）；University of Copenhagen（哥本哈根大学）；University of Maryland（马里兰大学）
Tom Hope, Ronen Tamari, Hyeonsu Kang, Daniel Hershcovich, Joel Chan, Aniket Kittur, Dafna Shahaf
Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations. However, idea descriptions are typically in the form of unstructured text, lacking key structure that is required for supporting creative innovation interactions. Prior work has explored idea representations that were either limited in expressivity, required significant manual effort from users, or dependent on curated knowledge bases with poor coverage. We explore a novel representation that automatically breaks up products into fine-grained functional aspects capturing the purposes and mechanisms of ideas, and use it to support important creative innovation interactions: functional search for ideas, and exploration of the design space around a focal problem by viewing related problem perspectives pooled from across many products. In user studies, our approach boosts the quality of creative search and inspirations, substantially outperforming strong baselines by 50-60%.
ThematicPlane: Bridging Tacit User Intent and Latent Spaces for Image Generation
Adobe Inc.（Adobe公司）；Johns Hopkins University（约翰霍普金斯大学）；University of Washington（华盛顿大学）；University of Colorado（科罗拉多大学）；University of Illinois at Urbana-Champaign（伊利诺伊大学厄巴纳-香槟分校）
NexusAI: Enabling Design Space Exploration of Ideas through Cognitive Abstraction and Functional Decomposition
Hong Kong University of Science and Technology（香港科技大学）；Hong Kong University of Science and Technology (Guangzhou)（香港科技大学（广州））；University of Michigan（密歇根大学）；Carnegie Mellon University（卡内基梅隆大学）
Suggestion Lists vs. Continuous Generation: Interaction Design for Writing with Generative Models on Mobile Devices Affect Text Length, Wording and Perceived Authorship
TaleFrame: An Interactive Story Generation System with Fine-Grained Control and Large Language Models
the College of Computer Science and Technology, Zhejiang University of Technology（浙江工业大学计算机科学与技术学院）；Zhejiang Key Laboratory of Visual Information Intelligent Processing（浙江省视觉信息智能处理重点实验室）
