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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ParseBench: A Document Parsing Benchmark for AI Agents · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2604.08538/</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/2604.08538/feed.xml" rel="self" type="application/rss+xml" /><item><title>ParseBench: A Document Parsing Benchmark for AI Agents — mentioned by pierre</title><link>https://news.ycombinator.com/item?id=47752297</link><guid isPermaLink="false">urn:hackerpapers:mention:2604.08538:47752297</guid><pubDate>Mon, 13 Apr 2026 14:14:02 GMT</pubDate><description>&lt;p&gt;Build a benchmark to evaluate how good document parser work on a dataset of 2000 PDFs manually annotated, trying to evaluate accross multiple dimensions: charts, tables, text styling, text correctness, and attribution. The benchmark evaluate performance on full page (not selected part of the pages), and evaluaye different OSS / crobtier model / commercial approach. For transparency it is available as a HF leaderbaord. Paper: https://arxiv.org/abs/2604.08538&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2604.08538/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
