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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Answering Questions about Data Visualizations using Efficient Bimodal Fusion · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1908.01801/</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/1908.01801/feed.xml" rel="self" type="application/rss+xml" /><item><title>Answering Questions about Data Visualizations using Efficient Bimodal Fusion — mentioned by chriskanan</title><link>https://news.ycombinator.com/item?id=22117256</link><guid isPermaLink="false">urn:hackerpapers:mention:1908.01801:22117256</guid><pubDate>Wed, 22 Jan 2020 13:17:54 GMT</pubDate><description>&lt;p&gt;With collaborators at Adobe Research, my lab published a paper recently showing how to do table reconstruction from infographics (e.g., bar charts) using deep learning [1]. While it isn&amp;#x27;t the sexiest project, I&amp;#x27;ve had a number of companies reach out about the project. Human written rule-based approaches are pretty bad at the task, and even humans doing it manually aren&amp;#x27;t great (likely due to sloppiness). [1] https://arxiv.org/abs/1908.01801&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1908.01801/"&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>
