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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2410.13863/</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/2410.13863/feed.xml" rel="self" type="application/rss+xml" /><item><title>Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens — mentioned by zaptrem</title><link>https://news.ycombinator.com/item?id=43480074</link><guid isPermaLink="false">urn:hackerpapers:mention:2410.13863:43480074</guid><pubDate>Wed, 26 Mar 2025 08:40:55 GMT</pubDate><description>&lt;p&gt;Token by token diffusion was done by MAR https://arxiv.org/abs/2406.11838 and Fluid (scaled up MAR) https://arxiv.org/abs/2410.13863 When you randomly pick the locations they found it worked okay, but doing it in raster order (left to right, top to bottom) they found it didn&amp;#x27;t work as well. We tried it for music and found it was vulnerable to compounding error and lots of oddness relating to the fragility of continuous space CFG.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2410.13863/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item></channel></rss>
