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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2412.18619/</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/2412.18619/feed.xml" rel="self" type="application/rss+xml" /><item><title>Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey — mentioned by leochen0124</title><link>https://news.ycombinator.com/item?id=42643939</link><guid isPermaLink="false">urn:hackerpapers:mention:2412.18619:42643939</guid><pubDate>Thu, 09 Jan 2025 10:47:23 GMT</pubDate><description>&lt;p&gt;Author here, We started writing this survey in early 2024, motivated by the idea that the Next Token Prediction paradigm could unify tasks across not just text but also image, audio, and video domains. At the time, works like Unified-IO received far less attention compared to language-focused LLMs. Fast forward to early 2025, we’re seeing more unified LMMs like Chameleon, Transfusion, and Grok (based on their respective descriptions) that integrate understanding and generation within a single model. This could indeed be the year where LLMs handle multimodal tasks—text, image, audio, and…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2412.18619/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
