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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2501.03895/</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/2501.03895/feed.xml" rel="self" type="application/rss+xml" /><item><title>LLaVA-Mini: Efficient Image and Video Large Multimodal Models with One Vision Token — mentioned by Vily</title><link>https://news.ycombinator.com/item?id=42679455</link><guid isPermaLink="false">urn:hackerpapers:mention:2501.03895:42679455</guid><pubDate>Mon, 13 Jan 2025 02:35:04 GMT</pubDate><description>&lt;p&gt;LLaVA-Miniis an efficient LMM for image/video understanding using 1 vision token, offering: (1)fast response (40ms per image), (2)less VRAM usage (support 3-hour video understanding on 24GB GPU). Paper: https://arxiv.org/abs/2501.03895 Code &amp;amp; Demo: https://github.com/ictnlp/LLaVA-Mini&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2501.03895/"&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>
