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Ivana Balazevic

@ibalazevic.bsky.social
974 followers 134 following 4 posts

Senior Research Scientist at Google DeepMind, working on Gemini. PhD from University of Edinburgh. ibalazevic.github.io

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Ivana Balazevic @ibalazevic.bsky.social · 18/12/2024
Disentanglement is an intriguing phenomenon that arises in generative latent variable models for reasons that are not fully understood. If you’re interested in learning why, I highly recommend giving Carl’s blog a read!
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Reposted by Ivana Balazevic
Aida Nematzadeh @aidanematzadeh.bsky.social · 06/12/2024
I am hiring for RS/RE positions! If you are interested in language-flavored multimodal learning, evaluation, or post-training apply here 🦎 boards.greenhouse.io/deepmind/job... I will also be #NeurIPS2024 so come say hi! (Please email me to find time to chat)
boards.greenhouse.io
Research Scientist, Language
London, UK
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Reposted by Ivana Balazevic
Lucas Beyer (bl16) @giffmana.ai · 03/12/2024
Our big_vision codebase is really good! And it's *the* reference for ViT, SigLIP, PaliGemma, JetFormer, ... including fine-tuning them. However, it's criminally undocumented. I tried using it outside Google to fine-tune PaliGemma and SigLIP on GPUs, and wrote a tutorial: lb.eyer.be/a/bv_tuto.html
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Reposted by Ivana Balazevic
Carl Allen @carl-allen.bsky.social · 02/12/2024
I think this comes down to the model behind p(x,y). If features of x cause y, e.g. aspects of a website (x) -> clicks (y); age/health -> disease, then p(y|x) is a (regression) fn of x. But if x|y is a distrib'n of different y's (e.g. cats) then p(y|x) is given by Bayes rule (squint at softmax).
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Reposted by Ivana Balazevic
Dima Damen @ECCV 2026 @dimadamen.bsky.social · 28/11/2024
Read our paper: Context-Aware Multimodal Pretraining Now on ArXiv Can you turn vision-language models into strong any-shot models? Go beyond zero-shot performance in SigLixP (x for context) Read @confusezius.bsky.social thread below… And follow Karsten … a rising star!
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Ivana Balazevic @ibalazevic.bsky.social · 28/11/2024
We maintain strong zero-shot transfer of CLIP / SigLIP across model size and data scale, while achieving up to 4x few-shot sample efficiency and up to +16% performance gains! Fun project with @confusezius.bsky.social, @zeynepakata.bsky.social, @dimadamen.bsky.social and @olivierhenaff.bsky.social.
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Reposted by Ivana Balazevic
Marc Lanctot @sharky6000.bsky.social · 25/11/2024
Just a heads up to everyone: @deep-mind.bsky.social is unfortunately a fake account and has been reported. Please do not follow it nor repost anything from it.
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