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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Flamingo: a Visual Language Model for Few-Shot Learning · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2204.14198/</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/2204.14198/feed.xml" rel="self" type="application/rss+xml" /><item><title>Flamingo: a Visual Language Model for Few-Shot Learning — mentioned by Animats</title><link>https://news.ycombinator.com/item?id=45442162</link><guid isPermaLink="false">urn:hackerpapers:mention:2204.14198:45442162</guid><pubDate>Wed, 01 Oct 2025 19:28:43 GMT</pubDate><description>&lt;p&gt;The underlying work is something called &amp;quot;Flamingo&amp;quot;.[1] This is a system for understanding interleaved text and images in sequence. So it can process two &amp;quot;modalities&amp;quot; that are both sequential. This new work seems to put some kind of time token in one &amp;quot;modality&amp;quot; channel, leading to more awareness of time. (The web site is too cute. Applying a left to right gradient on text is a bit much.) [1] https://arxiv.org/pdf/2204.14198&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2204.14198/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>Flamingo: a Visual Language Model for Few-Shot Learning — mentioned by famouswaffles</title><link>https://news.ycombinator.com/item?id=39468629</link><guid isPermaLink="false">urn:hackerpapers:mention:2204.14198:39468629</guid><pubDate>Thu, 22 Feb 2024 15:36:03 GMT</pubDate><description>&lt;p&gt;This explanation is wrong as I&amp;#x27;ve already said (256 is not the result of any conversion to text) but no one has to take my word for it. From the Gemini report https://arxiv.org/abs/2312.11805 &amp;gt;The visual encoding of Gemini models is inspired by our own foundational work on Flamingo (Alayrac et al., 2022), CoCa (Yu et al., 2022a), and PaLI (Chen et al.,2022), with the important distinction that the models are multimodal from the beginning and can natively output images using discrete image tokens (Ramesh et al., 2021; Yu et al., 2022b). These are the papers Google say the multimodality in…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2204.14198/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CV</category></item><item><title>Flamingo: a Visual Language Model for Few-Shot Learning — mentioned by edouard-harris</title><link>https://news.ycombinator.com/item?id=31360156</link><guid isPermaLink="false">urn:hackerpapers:mention:2204.14198:31360156</guid><pubDate>Thu, 12 May 2022 21:10:33 GMT</pubDate><description>&lt;p&gt;That Tim Urban piece is great. It&amp;#x27;s also an interesting time capsule in terms of which AI problems were and were not considered hard in 2015 (when the post was written). From the post: &amp;gt; Build a computer that can multiply two ten-digit numbers in a split second—incredibly easy. Build one that can look at a dog and answer whether it’s a dog or a cat—spectacularly difficult. Make AI that can beat any human in chess? Done. Make one that can read a paragraph from a six-year-old’s picture book and not just recognize the words but understand the meaning of them? Google is currently spending…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2204.14198/"&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>
