PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916851791953920 |
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| author | Zhang, Runhua Ouyang, Yang Shen, Leixian Tang, Yuying Ma, Xiaojuan Qu, Huamin Xu, Xian |
| author_facet | Zhang, Runhua Ouyang, Yang Shen, Leixian Tang, Yuying Ma, Xiaojuan Qu, Huamin Xu, Xian |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_14527 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration Zhang, Runhua Ouyang, Yang Shen, Leixian Tang, Yuying Ma, Xiaojuan Qu, Huamin Xu, Xian Human-Computer Interaction 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. |
| title | PaperBridge: Crafting Research Narratives through Human-AI Co-Exploration |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2507.14527 |