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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-Domain Evaluation Framework for Academic Documents · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2303.09957/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2303.09957/feed.xml" rel="self" type="application/rss+xml" /><item><title>A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-Domain Evaluation Framework for Academic Documents — mentioned by freethejazz</title><link>https://news.ycombinator.com/item?id=41208406</link><guid isPermaLink="false">urn:hackerpapers:mention:2303.09957:41208406</guid><pubDate>Sat, 10 Aug 2024 09:51:37 GMT</pubDate><description>&lt;p&gt;Depending on how much structure you want to extract before passing the pdf contents to the next step in your pipeline, this paper[1] might be helpful in surfacing more options. It&amp;#x27;s a review/benchmark of numerous tools applied to the information extraction of academic documents. I haven&amp;#x27;t been through to evaluate the solutions they examined, but it&amp;#x27;s how I discovered GROBID and IMO lays out the strengths of each approach clearly. [1] https://arxiv.org/pdf/2303.09957&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2303.09957/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.IR</category></item></channel></rss>
