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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2310.15308/</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/2310.15308/feed.xml" rel="self" type="application/rss+xml" /><item><title>SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding — mentioned by zerojames</title><link>https://news.ycombinator.com/item?id=38026107</link><guid isPermaLink="false">urn:hackerpapers:mention:2310.15308:38026107</guid><pubDate>Thu, 26 Oct 2023 14:31:19 GMT</pubDate><description>&lt;p&gt;I just posted a comment :D I work for a computer vision company. I use CLIP almost every day. Example use cases for which I have used CLIP: - Image classification - Automated labeling for classification models - Image clustering - Gathering images for model training that are sufficiently dissimilar from existing samples - Content moderation CLIP is also being used widely in new research. SAM-CLIP, shared with me by my manager today, is using CLIP (https://arxiv.org/abs/2310.15308) and knowledge distillation for training a new model. I have seen references to CLIP throughout multimodal LLM…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2310.15308/"&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>
