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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2304.10592/</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/2304.10592/feed.xml" rel="self" type="application/rss+xml" /><item><title>MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models — mentioned by mk_stjames</title><link>https://news.ycombinator.com/item?id=37882544</link><guid isPermaLink="false">urn:hackerpapers:mention:2304.10592:37882544</guid><pubDate>Sat, 14 Oct 2023 17:44:41 GMT</pubDate><description>&lt;p&gt;The entire GPT4 model was not retrained to utilize images, instead I think it is much more like show in [1] where an extra layer(s) are learned that take another pretrained image model and map that model to the latent space of the LLM. In [1] this was just a single linear layer. I found it pretty shocking how simple it was. I believe OpenAI is doing something similar. [1] https://arxiv.org/pdf/2304.10592.pdf&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2304.10592/"&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>
