<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1705.10843/</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/1705.10843/feed.xml" rel="self" type="application/rss+xml" /><item><title>Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models — HN submission</title><link>https://news.ycombinator.com/item?id=14477487</link><guid isPermaLink="false">urn:hackerpapers:submission:1705.10843:14477487</guid><pubDate>Sat, 03 Jun 2017 17:48:09 GMT</pubDate><description>&lt;p&gt;Show HN: Objective-Reinforced GANs&lt;/p&gt;&lt;p&gt;A new GAN is in town! A combination of RL + Generative Adversarial Networks that lets you specify objectives for generating data. For example: &amp;quot;I&amp;#x27;d like my generated poems to have fancier words&amp;quot; or &amp;quot;I&amp;#x27;d like my generated molecules to have higher solubility.&amp;quot; Define simple rewards and ORGAN biases the generative model for you. arXiv: https://arxiv.org/abs/1705.10843 GitHub: https://github.com/gablg1/ORGAN&lt;/p&gt;&lt;p&gt;3 points; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/1705.10843/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>stat.ML</category></item></channel></rss>
