Satya Narayan Shukla (@imsnshukla) 's Twitter Profile
Satya Narayan Shukla

@imsnshukla

Senior Research Scientist @MetaAI | PhD @UMassAmherst | Prev @MSFTResearch, @facebookai and @Bosch_AI | BTech @IITKgp

ID: 2197194733

linkhttps://satyanshukla.github.io/ calendar_today16-11-2013 06:04:48

33 Tweet

213 Followers

658 Following

Satya Narayan Shukla (@imsnshukla) 's Twitter Profile Photo

I'll be presenting this work at #KDD2021 in the research paper session on 08/17 at 1:30 pm EST and in the poster session on 08/18 at 5:30 pm EST. Please feel free to drop by if you're attending, or ping me if you have any questions!

Satya Narayan Shukla (@imsnshukla) 's Twitter Profile Photo

10 days to submit to our #NeurIPS workshop "Learning from Time Series for Health". Checkout our website: timeseriesforhealth.github.io Can't wait to see your amazing work and meet you in person in December!

Tom Hartvigsen (@tom_hartvigsen) 's Twitter Profile Photo

By popular demand, we've extended the submission deadline for the #NeurIPS2022 Workshop on Learning from Time Series for Health to September 30th!

AI at Meta (@aiatmeta) 's Twitter Profile Photo

We’re pleased to introduce Make-A-Video, our latest in #GenerativeAI research! With just a few words, this state-of-the-art AI system generates high-quality videos from text prompts. Have an idea you want to see? Reply w/ your prompt using #MetaAI and we’ll share more results.

Kanchana Ranasinghe (@kahnchana) 's Twitter Profile Photo

Our paper on “Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs” accepted to CVPR ‘24. Arxiv: arxiv.org/abs/2404.07449

Our paper on “Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs” accepted to CVPR ‘24. 

Arxiv: arxiv.org/abs/2404.07449
Lucas Bandarkar (@lucasbandarkar) 's Twitter Profile Photo

We presented Belebele at ACL 2024 this week! (Thx to Davis Liang and Satya Narayan Shukla) A year on from its release, it’s been really cool to see the diversity of research projects that have used it. The field is in dire need of more multilingual benchmarks !

Saining Xie (@sainingxie) 's Twitter Profile Photo

Our take on a 4o-style AR + diffusion unified model: Transferring knowledge from an AR LLM to generation is easier than expected--you don't even need to touch the LLM. The right bridge between output modalities can unlock cool capabilities like knowledge-augmented generation!

Satya Narayan Shukla (@imsnshukla) 's Twitter Profile Photo

Check out our latest work on training unified understanding and generation models. We show that frozen MLLMs can seamlessly transfer knowledge, reasoning, and in-context learning from text to pixel output.