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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>ScalableViT: Rethinking the Context-oriented Generalization of Vision Transformer · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2203.10790/</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/2203.10790/feed.xml" rel="self" type="application/rss+xml" /><item><title>ScalableViT: Rethinking the Context-oriented Generalization of Vision Transformer — mentioned by EnricoShippole</title><link>https://news.ycombinator.com/item?id=32058497</link><guid isPermaLink="false">urn:hackerpapers:mention:2203.10790:32058497</guid><pubDate>Mon, 11 Jul 2022 16:43:22 GMT</pubDate><description>&lt;p&gt;An open-source implementation of the ScalableViT: Rethinking the Context-oriented Generalization of Vision Transformer research paper in Google&amp;#x27;s JAX and Flax. &amp;quot;The vanilla self-attention mechanism inherently relies on pre-defined and steadfast computational dimensions. Such inflexibility restricts it from possessing context-oriented generalization that can bring more contextual cues and global representations. To mitigate this issue, we propose a Scalable Self-Attention (SSA) mechanism that leverages two scaling factors to release dimensions of query, key, and value matrix while unbinding…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2203.10790/"&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>
