Hammer PDF: An Intelligent PDF Reader for Scientific Papers
Sheng-Fu Wang, Shu-Hang Liu, Tian-Yi Che, Yi-Fan Lu, Song-Xiao Yang,, Heyan Huang, Xian-Ling Mao

TL;DR
Hammer PDF is an advanced PDF reader designed for scientific papers that enhances content understanding, information extension, and provides integrated academic search and Q&A features to improve researchers' reading efficiency.
Contribution
It introduces a multi-functional PDF reader with content extraction, extension capabilities, and integrated academic search and Q&A, addressing limitations of traditional PDF readers.
Findings
Supports locating and marking key terms and entities.
Provides relevant academic content like citations, videos, and blogs.
Includes a built-in academic search engine and Q&A bot.
Abstract
It is the most important way for researchers to acquire academic progress via reading scientific papers, most of which are in PDF format. However, existing PDF Readers like Adobe Acrobat Reader and Foxit PDF Reader are usually only for reading by rendering PDF files as a whole, and do not consider the multi-granularity content understanding of a paper itself. Specifically, taking a paper as a basic and separate unit, existing PDF Readers cannot access extended information about the paper, such as corresponding videos, blogs and codes. Meanwhile, they cannot understand the academic content of a paper, such as terms, authors, and citations. To solve these problems, we introduce Hammer PDF, an intelligent PDF Reader for scientific papers. Apart from basic reading functions, Hammer PDF has the following four innovative features: (1) information extraction ability, which can locate and mark…
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Taxonomy
TopicsWeb Data Mining and Analysis · Topic Modeling · Scientific Computing and Data Management
