​​Hey Nerd, join the Herd!... for a little book/paper review.

​​WHAT TO EXPECT

​​Each week we pick a paper to cover in depth and have open Q/A. Often joined by paper authors themselves! Reading is optional 🙃.

​THIS WEEK

​We present... Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

​TRY OUR NEW MODEL EVALS FEATURE

​Oxen.ai makes it easier than ever to prompt various models on real world datasets. Just like the paper, we run through prompts live and testing them on a variety of benchmarks.

​ARXIV DIVE SPECIAL. Email us via the link below and we'll 2x your free compute credits! All you gotta do is ask :) [one per user]

​🆓 🤖 Get Free Compute on Oxen 🤖 🆓

​Docs here (https://docs.oxen.ai/getting-started/models)

​💬 ​JOIN THE CONVO

​Discord here to share paper recs and more community discussion.

​​SEE PAST SESSIONS

​​To see past topics head over to our blog which has show notes and links to Youtube videos.
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​​WHO'S AN ARXIV DIVER

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​Team Oxen.ai is paying out a $5k referral bonus to anyone that helps us find our next Herd member. We’re looking for someone who’s a deep rustacean, optimization guru, and ideally has worked in the storage space before (think Dropbox). Send referrals to hello@oxen.ai. 

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​​About Oxen.ai: Build World-Class AI Datasets, Together. Track, iterate, collaborate on, & discover data in any format.

​​About Arxiv Dives

​​Each week we dive deep into a topic in machine learning or artificial intelligence. We break down the content into a digestible format and have an open discussion with the Oxen.ai community. Read more in our Arxiv Dive Manifesto.