🎥Our new video generative model, LTX-Video was release and open sourced!🚀🤩 👇

🚀 Big news for #VisualRiddles! We’re excited to announce that Visual Riddles has been accepted to the Creative AI Track at NeurIPS 2024! 🎉 Come explore our Visual Riddles Gallery—a showcase of cognitive and visual challenges for multimodal AI. 🧵

🚨 Happening NOW at #NeurIPS2024 with nitzan guetta ! 🎭 #VisualRiddles: A Commonsense and World Knowledge Challenge for Vision-Language Models. 📍 East Ballroom C, Creative AI Track 🔍 visual-riddles.github.io

New preprint! ✨ Interested in LLM-as-a-Judge? Want to get the best judge for ranking your system? our new work is just for you: "JuStRank: Benchmarking LLM Judges for System Ranking" 🕺💃 arxiv.org/abs/2412.09569

[1/8] Recent work has shown impressive Image-to-Video (I2V) generation results. However, accurately articulating multiple interacting objects and complex motions remains challenging. In our new work, we take a step toward addressing this challenge.

I'm happy to share that Stable Flow has been accepted to #CVPR2025 🥳 Source code is available at omriavrahami.com/stable-flow/

Care about LLM evaluation? 🤖 🤔 We bring you🕊️ DOVE a massive (250M!) collection of LLMs outputs On different prompts, domains, tokens, models... Join our community effort to expand it with YOUR model predictions & become a co-author!

In our #ICLR2025 paper, we introduce WIND 🌬️ A method that embeds a distortion watermark directly in the diffusion noise! Our method ensures that the watermark in one image does not reveal information about the watermark in other images 🤫 📝 arxiv.org/abs/2412.04653 (1/5)

I'm excited about the recent feature we've been working on at Pika - action editing! 🏃 📹 Video editing methods often focus on spatial edits. Our method can directly edit the *action* of objects, even when the video already contains a distinctive motion (e.g, 👋).

🚀 Excited to share OmnimatteZero: Training-Free Real-Time Omnimatte with Video Diffusion Models! 📄 Paper: arxiv.org/abs/2503.18033 🌐 Project: dvirsamuel.github.io/omnimattezero.… 🧵👇

RefVNLI Towards Scalable Evaluation of Subject-driven Text-to-image Generation

Think your latent-noise diffusion watermarking method is robust? Think again! We show that they are susceptible to adversarial attacks that only require one watermarked example and an off-the-shelf encoder. This attack can forge and remove the watermark with very high accuracy

🎉 Our paper DOVE 🕊️ has been accepted to #ACL2025 Findings! DOVE 🕊️ is a massive collection (250M!) of LLM outputs across different prompts, domains, and models, aimed at democratizing LLM evaluation research! Thanks to all collaborators! Paper: slab-nlp.github.io/DOVE/

I'm very excited to announce our #SIGGRAPH2025 workshop: Drawing & Sketching: Art, Psychology, and Computer Graphics 🎨🧠🫖 🔗 lines-and-minds.github.io 📅 Sunday, August 10th Join us to explore how people draw, how machines draw, and how the two might draw together! 🤖✍️

[1/6] 🎬 New paper: Story2Board We guide diffusion models to generate consistent, expressive storyboards--no training needed. By mixing attention-aligned tokens across panels, we reinforce character identity without hurting layout diversity. 🌐 daviddinkevich.github.io/Story2Board