PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration
PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration
Researchers frequently need to synthesize their own publications into coherent narratives that demonstrate their scholarly contributions. To suit diverse communication contexts, exploring alternative ways to organize one's work while maintaining coherence is particularly challenging, especially in interdisciplinary fields like HCI where individual researchers' publications may span diverse domains and methodologies. In this paper, we present PaperBridge, a human-AI co-exploration system informed by a formative study and content analysis. PaperBridge assists researchers in exploring diverse perspectives for organizing their publications into coherent narratives. At its core is a bi-directional analysis engine powered by large language models, supporting iterative exploration through both top-down user intent (e.g., determining organization structure) and bottom-up refinement on narrative components (e.g., thematic paper groupings). Our user study (N=12) demonstrated PaperBridge's usability and effectiveness in facilitating the exploration of alternative research narratives. Our findings also provided empirical insights into how interactive systems can scaffold academic communication tasks.
Runhua Zhang、Yang Ouyang、Leixian Shen、Yuying Tang、Xiaojuan Ma、Huamin Qu、Xian Xu
信息传播、知识传播计算技术、计算机技术
Runhua Zhang,Yang Ouyang,Leixian Shen,Yuying Tang,Xiaojuan Ma,Huamin Qu,Xian Xu.PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration[EB/OL].(2025-07-19)[2025-08-18].https://arxiv.org/abs/2507.14527.点此复制
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