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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2505.23705/</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/2505.23705/feed.xml" rel="self" type="application/rss+xml" /><item><title>Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better — mentioned by ACCount37</title><link>https://news.ycombinator.com/item?id=49155448</link><guid isPermaLink="false">urn:hackerpapers:mention:2505.23705:49155448</guid><pubDate>Mon, 03 Aug 2026 13:20:18 GMT</pubDate><description>&lt;p&gt;Read. The. Papers. https://arxiv.org/pdf/2505.23705 https://www.pi.website/download/pistar06.pdf https://www.pi.website/download/pi07.pdf The thing literally has a diffusion &amp;quot;action expert&amp;quot; sit in the same attention system as a pre-trained VLM. And the VLM itself is ALSO trained to generate raw actions as a part of the training recipe (the first paper) - it just doesn&amp;#x27;t do it at inference time. What the &amp;quot;action expert&amp;quot; does is parallelize the action generation process - based on VLM&amp;#x27;s internal states. It&amp;#x27;s exactly the thing you claimed to be impossible. Described in detail in a paper from…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2505.23705/"&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>
