Ondrej Bohdal

[Tech Blog] LoRA.rar uses a hypernetwork to merge content and style LoRAs in real-time, outperforming ZipLoRA in speed and quality. Trained on diverse pairs, it generalizes to unseen combinations, making it perfect for edge devices. #AI #LoRA #ImageGen research.samsung.com/blog/LoRA-rar-…

Our paper LoRA.rar just won the Best Paper Award at the P13N: Personalization in Generative AI Workshop @ ICCV 2025! 🎉 📄 Check it out here: arxiv.org/abs/2412.05148

🚀Exciting news, 𝗟𝗼𝗥𝗔.𝗿𝗮𝗿 has been accepted to @ICCVConference, which will be held in October in Hawaii🌈. Huge thanks to the team: @OBohdal, Mete Ozay, Pietro Zanuttigh, and @umbertomichieli. 📜Preprint: arxiv.org/abs/2412.05148 💻Code: github.com/donaldssh/LoRA…

Our VL-ICL bench is accepted to @iclr_conf! It's been almost a year since we developed it yet state-of-the-art VLMs still struggle on learning in-context. Great to work with @OBohdal and @tmh31.

🛸Excited to release 𝗟𝗼𝗥𝗔.𝗿𝗮𝗿, a groundbreaking method for personalized content and style image generation 🦕. 📜 Paper and video: arxiv.org/abs/2412.05148 huggingface.co/papers/2412.05… Huge thanks to the co-authors: @OBohdal, Mete Ozay, Pietro Zanuttigh, and @umbertomichieli

🚨FairTune: Optimizing PEFT for Fairness in Medical Image Analysis A new framework to finetune your large vision models that improves downstream fairness. Accepted in #ICLR2024 ✨ With: @OBohdal @STsaftaris @tmh31 CC: @vivnat @alvarezvalle @fepegar_ @BoWang87 @BioMedAI_CDT

Your #VLLMs are capable, but they are not safe enough! We present the first safety fine-tuning dataset VLGuard for VLLMs. By fine-tuning on it, the safety of VLLMs can be substantially improved while maintaining helpfulness. Check here for more details: ys-zong.github.io/VLGuard/

I am thrilled to share our latest paper, "Navigating Noise: A Study of How Noise Influences Generalisation and Calibration of Neural Networks openreview.net/forum?id=zn3fB…," published in @TmlrOrg, This work is a collective effort by @OBohdal , @tmh31, @mrd_rodrigues and myself :).

Evaluating the capabilities of multimodal in-context learning of #VLLMs? You can do better than VQA and captioning! Introducing *VL-ICL Bench* for both image-to-text and text-to-image #ICL. Project page: ys-zong.github.io/VL-ICL/

Your #VLLMs are capable, but they are not safe enough! We present the first safety fine-tuning dataset VLGuard for VLLMs. By fine-tuning on it, the safety of VLLMs can be substantially improved while maintaining helpfulness. Check here for more details: ys-zong.github.io/VLGuard/

🚨FairTune: Optimizing PEFT for Fairness in Medical Image Analysis A new framework to finetune your large vision models that improves downstream fairness. Accepted in #ICLR2024 ✨ With: @OBohdal @STsaftaris @tmh31 CC: @vivnat @alvarezvalle @fepegar_ @BoWang87 @BioMedAI_CDT