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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Think Again Networks and the Delta Loss · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1904.11816/</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/1904.11816/feed.xml" rel="self" type="application/rss+xml" /><item><title>Think Again Networks and the Delta Loss — mentioned by atrudeau</title><link>https://news.ycombinator.com/item?id=45517307</link><guid isPermaLink="false">urn:hackerpapers:mention:1904.11816:45517307</guid><pubDate>Wed, 08 Oct 2025 15:33:34 GMT</pubDate><description>&lt;p&gt;Very cool to see the effectiveness of recurrence on ARC. For those interested in recurrence, here are other works that leverage a similar approach for other types of problems: Language modeling: Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach https://arxiv.org/pdf/2502.05171 Puzzle solving: A Simple Loss Function for Convergent Algorithm Synthesis using RNNs https://openreview.net/pdf?id=WaAJ883AqiY End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking https://arxiv.org/abs/2202.05826 Can You Learn an Algorithm?…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1904.11816/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
