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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2503.18943/</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/2503.18943/feed.xml" rel="self" type="application/rss+xml" /><item><title>SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding — mentioned by Terretta</title><link>https://news.ycombinator.com/item?id=44997167</link><guid isPermaLink="false">urn:hackerpapers:mention:2503.18943:44997167</guid><pubDate>Sat, 23 Aug 2025 16:45:22 GMT</pubDate><description>&lt;p&gt;Paper: SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding: “We introduce SlowFast-LLaVA-1.5 (abbreviated as SF-LLaVA-1.5), a family of video large language models (LLMs) offering a token-efficient solution for long-form video understanding... Experimental results demonstrate that SF-LLaVA-1.5 achieves superior performance on a wide range of video and image tasks, with robust results at all model sizes (ranging from 1B to 7B). Notably, SF-LLaVA-1.5 achieves state-of-the-art results in long-form video understanding (e.g., LongVideoBench…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2503.18943/"&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>
