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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2203.02053/</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/2203.02053/feed.xml" rel="self" type="application/rss+xml" /><item><title>Mind the Gap: Understanding the Modality Gap in Multi-modal Contrastive Representation Learning — mentioned by bluejay2387</title><link>https://news.ycombinator.com/item?id=50108530</link><guid isPermaLink="false">urn:hackerpapers:mention:2203.02053:50108530</guid><pubDate>Thu, 15 Oct 2026 18:58:00 GMT</pubDate><description>&lt;p&gt;The claims seem to be an overreach of what is actually proven. We&amp;#x27;ve known about progressive feature complexity and the impacts of early training structures on later training for a really long time (since CNN&amp;#x27;s, The Lottery Ticket Hypothesis, etc...) and neither of those phenomenon are mutually exclusive with parameter overloading. The Multimodal Gap work (https://arxiv.org/abs/2203.02053) seems to imply networks have a tendency towards condensed representations that are clearly not semantic and a bunch of other considerations are already on the table for discussion. I don&amp;#x27;t think these have…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2203.02053/"&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>
