  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 spans like terms and
other entities; (2) information extension ability, which can present relevant
academic content of a paper, such as citations, references, codes, videos,
blogs; (3) built-in Hammer Scholar, an academic search engine based on academic
information collected from major academic databases; (4) built-in Q&A bot,
which can find helpful conference information. The proposed Hammer PDF Reader
can help researchers, especially those studying computer science, to improve
the efficiency and experience of reading scientific papers. We have released
Hammer PDF, available at https://pdf.hammerscholar.net/face.
