Vision transformers need registers! Or at least, it seems they 𝘸𝘢𝘯𝘵 some… ViTs have artifacts in attention maps. It’s due to the model using these patches as “registers”. Just add new tokens (“[reg]”): - no artifacts - interpretable attention maps 🦖 - improved performances!

“Write me a scientific review in the voice of Dr. Seuss and as reviewer 2, the negative reviewer who clearly doesn’t understand the paper and has probably not read the paper. Mention that there is no novelty and that the contribution is limited.” GPT-4: Oh, I've read your work,

Thanks AK for promoting our work! With GaLore, now it is possible to pre-train a 7B model in NVidia RTX 4090s with 24G memory! 🤔How? Instead of assuming low-rank weight structure like LoRA, we show that the weight gradient is naturally low-rank and thus can be

Wow that’s cool! LoRA but for training.

I can’t find a recent paper (and tweet) that had emojis all over an image. I think it was a method about interpreting (possibly segmenting) images with/from diffusion models. Can somebody help?

✨🎨🏰Super excited to share our new paper Ensemble everything everywhere: Multi-scale aggregation for adversarial robustness Inspired by biology we 1) get adversarial robustness + interpretability for free, 2) turn classifiers into generators & 3) design attacks on vLLMs 1/12

I received feedback that my post about reviews not being "random" caused stress for some students. I'm sorry for that. It was meant to be empowering. Personally, I find the idea that I don't have some control over the destiny of my papers to be disheartening. If the process is

Checkout PromptMap, presented at IUI'25, a new interaction style with text-to-image models/data that allows users to freely explore a vast collection of synthetic prompts through a map-like view with semantic zoom. Paper: arxiv.org/abs/2503.09436 Code: github.com/Bill2462/promp…

Happy to share that TKG-DM, a training-free chroma key content generation diffusion model was accepted to CVPR 25. Project led by OguRyu🇩🇪 Paper: arxiv.org/abs/2411.15580 Code: github.com/ryugo417/TKG-DM

Say hello to DINOv3 🦖🦖🦖 A major release that raises the bar of self-supervised vision foundation models. With stunning high-resolution dense features, it’s a game-changer for vision tasks! We scaled model size and training data, but here's what makes it special 👇

Unifying VXAI: A Systematic Review and Framework for the Evaluation of Explainable AI David Dembinsky, Adriano Lucieri, Stanislav Frolov, Hiba Najjar, Ko Watanabe, Andreas Dengel. Action editor: Krikamol Muandet. openreview.net/forum?id=wAvFL… #explanation

Happy to share our VXAI paper at TMLR, a review & framework for the evaluation of XAI. Check out the VXAI explorer here vxai.dfki.de