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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2406.16860/</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/2406.16860/feed.xml" rel="self" type="application/rss+xml" /><item><title>Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs — mentioned by fpgaminer</title><link>https://news.ycombinator.com/item?id=42978593</link><guid isPermaLink="false">urn:hackerpapers:mention:2406.16860:42978593</guid><pubDate>Fri, 07 Feb 2025 23:13:38 GMT</pubDate><description>&lt;p&gt;A lot of problems jump out to me with this article, particularly with the explanation of multi-modal LLMs. I&amp;#x27;ll say that I _do_ agree with the thrust of the article. Don&amp;#x27;t trust LLMs. But they probably should have argued legitimate issues with VLM based OCR, rather than try to talk about how VLMs are somehow fundamentally flawed or something. &amp;gt; LLMs process images through high-dimensional embeddings, essentially creating abstract representations that prioritize semantic understanding over precise character recognition. This isn&amp;#x27;t true. CLIP and its derivatives don&amp;#x27;t prioritize semantic…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2406.16860/"&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>Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs — mentioned by tucnak</title><link>https://news.ycombinator.com/item?id=42845254</link><guid isPermaLink="false">urn:hackerpapers:mention:2406.16860:42845254</guid><pubDate>Mon, 27 Jan 2025 20:28:09 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;m still not sure why they keep LeCun at Facebook; his single most-cited contribution to the field in 2024 has been with NYU[0], not Facebook. What is his role at Facebook exactly, has he explained it? I recall him making all the wrong predictions in 2023 what&amp;#x27;s changed? Chollet is similarly a mystery to me; it feels like these guys were busy riffing CNN&amp;#x27;s when the Transformer came about and since then have been trying to far-out in search of gold. [0]: https://arxiv.org/abs/2406.16860&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2406.16860/"&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>Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs — mentioned by ellisbrown</title><link>https://news.ycombinator.com/item?id=40793387</link><guid isPermaLink="false">urn:hackerpapers:mention:2406.16860:40793387</guid><pubDate>Tue, 25 Jun 2024 20:46:16 GMT</pubDate><description>&lt;p&gt;arXiv: https://arxiv.org/abs/2406.16860 Website: https://cambrian-mllm.github.io Code: https://github.com/cambrian-mllm/cambrian Checkpoints: https://huggingface.co/collections/nyu-visionx/cambrian-1-mo... Data: https://huggingface.co/collections/nyu-visionx/cambrian-data... Benchmark: https://huggingface.co/datasets/nyu-visionx/CV-Bench&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2406.16860/"&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>
