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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Horizon Reduction Makes RL Scalable · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2506.04168/</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/2506.04168/feed.xml" rel="self" type="application/rss+xml" /><item><title>Horizon Reduction Makes RL Scalable — mentioned by isaacimagine</title><link>https://news.ycombinator.com/item?id=44283844</link><guid isPermaLink="false">urn:hackerpapers:mention:2506.04168:44283844</guid><pubDate>Sun, 15 Jun 2025 17:58:11 GMT</pubDate><description>&lt;p&gt;TFP: https://arxiv.org/abs/2506.04168 The DT citation [10] is used on a single line, in a paragraph listing prior work, as an &amp;quot;and more&amp;quot;. Another paper that uses DTs [53] is also cited in a similar way. The authors do not test or discuss DTs. &amp;gt; hardness of the credit assignment ... data sparsity. That is true, but not the point I&amp;#x27;m making. &amp;quot;Bypassing credit assignment&amp;quot;, in the context of long-horizon task modeling, is a statement about using attention to allocate long-horizon reward without horizon-reducing discount, not architecture choice. To expand: if I have an environment with a key that…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2506.04168/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
