Nir Goren đã retweet
We developed a simple, sample-efficient online RL technique for post-training image generation models. We see it as a possible steerable alternative to CFG, driven by any scalar reward, including human preference.
English
Nir Goren
245 posts
Nir Goren
@nirgoren
Researching AI https://t.co/eMCNT73s4T
Tham gia Mayıs 2018
117 Đang theo dõi115 Người theo dõi
English
English
CVPR 2026 highlight! 🔥
In this work co-led with @YehezkelShai, we show that a plain diffusion model can solve hard geometry problems by treating them as conditional image generation problems. No special architecture needed.
w/ @OmerDahary, @kusichan, @OPatashnik, @DanielCohenOr1
Shai Yehezkel@YehezkelShai
Visual Diffusion Models are Geometric Solvers We cast geometry as images: a plain diffusion model denoises into valid solutions. It is simple, general and effective. Shown on Inscribed Square, Steiner Tree, and Maximum Area Polygonization - all classic hard problems.
English
Nir Goren đã retweet
[1/5] Is Text Enough for Control? 🐇
Text-driven video editing lets you describe *what* to change. But what about *how much*?
We introduce Adaptive-Origin Guidance (AdaOr).
A joint work with @DecartAI and @TelAvivUni 🧪
accepted to #SIGGRAPH2026.
English
Nir Goren đã retweet
Video models as Physics simulators. 🌍🎥
[1/] In our latest work, WinDiNet, we finetuned a pre-trained video model into a differentiable physics engine. 1000x faster than traditional CFD solvers.
Project page: rbischof.github.io/windinet_web/
Abs: arxiv.org/abs/2603.21210
English
Nir Goren đã retweet
Our previous intern released an extremely impressive re-implemented demo of our paper on multiplayer diffusion game engines.
play-multigen.com
I think this might be the first time you can play a fully-functional multiplayer generative game online with other people. 🤯
English
Nir Goren đã retweet
Modern T2I DiTs are incredibly powerful, but have a serious diversity problem.
We introduce a surprisingly simple and efficient inference-time fix
(+2s for Flux-dev, +1s for SD3.5-Turbo).
Excited to share our SIGGRAPH 2026 (conditional) paper:
“On-the-fly Repulsion in the Contextual Space for Rich Diversity in Diffusion Transformers”
English
Nir Goren đã retweet
Excited to share that our work, “Image Generation from Contextually Contradictory Prompts,” was accepted to CVPR 2026 🎉
Diffusion models fail on some seemingly simple prompts.
Why do they ignore what you asked for?
We show why, and how to fix it with a simple, training-free method.
Joint work with @OPatashnik @OmerDahary @MokadyRon @DanielCohenOr1
English
Nir Goren đã retweet
DLSS 5 is all over the timeline, and for good reason. In my internship at @AIatMeta we had the same idea: use a video model as a learned second-stage renderer on top of game engines. In our paper RealMaster, we make synthetic video look real while preserving scene fidelity 👇
English
Nir Goren đã retweet
Video editing just got more dynamic! 🚀
Thrilled to share DynaEdit: a training-free, text-based method for non-rigid video editing.
Work done during my internship at @GoogleDeepMind with @Roni_Paiss, @kusichan, @inbar_mosseri, @talidekel, @t_michaeli
dynaedit.github.io
English
@PolaczekSagi {
"hooks": {
"Notification": [
{
"matcher": "",
"hooks": [
{
"type": "command",
"command": "printf '\\a' > $(tmux display-message -p '#{pane_tty}')"
}
]
}
]
}
English
@PolaczekSagi btw, you can set up ~/.claude/settings.json for a terminal bell on completion/permission request that works over claude code in tmux (which you can turn into a system notification on iTerm2 when not in focus):
English
iTerm2 + 'tmux -CC'
best settings for persistent remote development I've been using so far. easily recovers remote sessions (e.g. claude) even when get disconnected - which happens often in the bomb shelters 👀
does anyone have a better one?
English
Nir Goren đã retweet
Nir Goren đã retweet
SemanticMoments - Semantic motion similarity
How do you find videos with similar motion?
It’s harder than it sounds.
Models like VideoMAE and V-JEPA encode motion, but their embeddings are dominated by appearance.
So how do we build a compact embedding for motion similarity?
Joint work with @kfir99 @OPatashnik @BenaimSagie @MokadyRon
GIF
English
English
@nirgoren @KatzirOren @abhinav_nakarmi @eyalr0 @mahmoods01 @OPatashnik Such an interesting paper! Congrats Nir! 👏
English
Happy to share that our paper "NoisePrints: Distortion-Free Watermarks for Authorship in Private Diffusion Models" has been accepted to ICLR 2026!
Huge thanks to my amazing co-authors:
@KatzirOren @abhinav_nakarmi @eyalr0 @mahmoods01 @OPatashnik
#ICLR2026 🇧🇷
Nir Goren@nirgoren
The initial noise in diffusion models is surprisingly correlated with the final image. Our NoisePrints paper exploits this to provide a lightweight, distortion-free, cryptographically secure watermark for proving authorship of generated images & videos, requiring no model access.
English
Nir Goren đã retweet
🚀 LTX-2 is now open source: text → audio + video.
Today we’re releasing LTX-2, the first open-source foundation model for joint audiovisual generation, together with a full technical report.
🧵👇
English
Nir Goren đã retweet
[1/4] Sync about it… 💭✨
Editing a portrait video yet keeping it fully synced with the original across the entire sequence.
Read more about Sync-LoRA: sagipolaczek.github.io/Sync-LoRA/ 🚀
English
Might be interesting to see how see training a diffusion network on the visual representation of ARC fares. We demonstrated that visual diffusion models are capable reasoners on some other hard tasks when they are represented as images: arxiv.org/abs/2510.21697
Rosinality@rosinality
You can just train ViT from scratch to solve ARC.
English