[HN Gopher] Liquid: Language models are scalable and unified mul...
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       Liquid: Language models are scalable and unified multi-modal
       generators
        
       Author : pr337h4m
       Score  : 41 points
       Date   : 2025-04-15 19:46 UTC (3 hours ago)
        
 (HTM) web link (foundationvision.github.io)
 (TXT) w3m dump (foundationvision.github.io)
        
       | Centigonal wrote:
       | I love the website for this paper! Each section asks a question,
       | and immediately answers it with a figure and a few sentences of
       | discussion. It's less tech-demo heavy than a lot of other paper
       | websites (those are cool, too, in their own way), and instead
       | focuses on characterizing multimodal model behavior in a nice,
       | clean, disciplined way.
        
       | swyx wrote:
       | hmm this is a tough name - conflicts with Liquid AI
       | https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que...
        
       | gwern wrote:
       | > For the first time, Liquid uncovers a scaling law that
       | performance drop unavoidably brought by the unified training of
       | visual and language tasks diminishes as the model size
       | increases...No prior work has explored whether LLMs retain the
       | power-law scaling laws observed in language tasks when extended
       | to visual generation tasks. We prove this alignment and further
       | show that vision can be effectively learned by LLMs as a form of
       | language.
       | 
       | Does this really show much that
       | https://arxiv.org/abs/2301.03728#facebook (uncited) and other
       | earlier work did not?
        
       | Nijikokun wrote:
       | it performs well with composition, however it seems SD and SDXL
       | excels in capability and quality when intermixed with pipelines
       | and workflows, this doesn't do much to talk about that comparison
       | and whenever i see things like this i think about the overall
       | workflow, like cool you do good composition but you don't fit
       | within the workflow or ecosystem that surrounds that tool and
       | thus i have low expectations around adoption
        
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       (page generated 2025-04-15 23:00 UTC)