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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LatentMoE: Toward Optimal Accuracy per FLOP and Parameter in Mixture of Experts · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2601.18089/</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/2601.18089/feed.xml" rel="self" type="application/rss+xml" /><item><title>LatentMoE: Toward Optimal Accuracy per FLOP and Parameter in Mixture of Experts — mentioned by buildbot</title><link>https://news.ycombinator.com/item?id=48935781</link><guid isPermaLink="false">urn:hackerpapers:mention:2601.18089:48935781</guid><pubDate>Thu, 16 Jul 2026 15:19:52 GMT</pubDate><description>&lt;p&gt;Amazing to see an open source model already nearing the benchmarks of Fable and GPT 5.6 Sol! Also very cool to see LatentMoE being picked up by more models (https://arxiv.org/abs/2601.18089)&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2601.18089/"&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>
