Unveiling the Power of Integration: Block Diagram Summarization through Local-Global Fusion

Shreyanshu Bhushan, Eun-Soo Jung, Minho Lee


Abstract
Block Diagrams play an essential role in visualizing the relationships between components or systems. Generating summaries of block diagrams is important for document understanding or question answering (QA) tasks by providing concise overviews of complex systems. However, it’s a challenging task as it requires compressing complex relationships into informative descriptions. In this paper, we present “BlockNet”, a fusion framework that summarizes block diagrams by integrating local and global information, catering to both English and Korean languages. Additionally, we introduce a new multilingual method to produce block diagram data, resulting in a high-quality dataset called “BD-EnKo”. In BlockNet, we develop “BlockSplit”, an Optical Character Recognition (OCR) based algorithm employing the divide-and-conquer principle for local information extraction. We train an OCR-free transformer architecture for global information extraction using BD-EnKo and public data. To assess the effectiveness of our model, we conduct thorough experiments on different datasets. The assessment shows that BlockNet surpasses all previous methods and models, including GPT-4V, for block diagram summarization.
Anthology ID:
2024.findings-acl.822
Volume:
Findings of the Association for Computational Linguistics: ACL 2024
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
13837–13856
Language:
URL:
https://aclanthology.org/2024.findings-acl.822
DOI:
10.18653/v1/2024.findings-acl.822
Bibkey:
Cite (ACL):
Shreyanshu Bhushan, Eun-Soo Jung, and Minho Lee. 2024. Unveiling the Power of Integration: Block Diagram Summarization through Local-Global Fusion. In Findings of the Association for Computational Linguistics: ACL 2024, pages 13837–13856, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Unveiling the Power of Integration: Block Diagram Summarization through Local-Global Fusion (Bhushan et al., Findings 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/dois-2013-emnlp/2024.findings-acl.822.pdf