Research lab led by @y_m_asano at @utn_nuremberg. We conduct fundamental AI research and develop core technology for future Foundation Models.

Nuremberg
Joined July 2024
FunAI retweeted
Replying to @FunAILab
@FunAILab with me and @dawkopi at @COLM_conf in SF! Seeing lots of cool papers already and stoked for meeting more folks from the LM side these days! Just reach out and let’s grab a coffee ✌️
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It’s #ECCV2026 Main Conference Day 2! Coming up later today: our second keynote with @ylecun, followed by the reception.
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FunAI retweeted
I am incredibly honoured to receive the ECVA/ @eccvconf Young Researcher Award. ✨🎉I cannot quite believe it, but what I do know is, that this is all thanks to my amazing collaborators, mentors and students and friends. Thank you! You all put the Fun in Fundamental AI. It’s an adventure to be in this field, in this time.
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ECVA Young Researcher Award winners 2025-2026
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FunAI retweeted
My opposing take: text will get you only so far (maybe far enough for many applications and commercial value), but learning from unlabeled data, in particular videos, will (with the right method/architecture) be the best: huge quantities, physics, geometry, occlusions etc. but: Getting there will take proper research, no winning recipe there just yet
Replying to @gabriberton
3. When asked about DINO (and SSL in general): "Text is there so why not use it? [...] I think it's an intellectually interesting concept and we should be able to learn good representations without text and it's nice that they got this far, but (not using text) it's unnecessarily making it hard" [3/3]
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FunAI retweeted
(1/n) What if you could teach a vision model about 3D structure without a single 3D label and just a tiny fraction of its pretraining compute? 👁️ That’s 3DPoV. ✨ Heading to #ICML2026 in Seoul 🇰🇷 to share it 👇
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FunAI retweeted
[PhD opening🎉] Part of the Bavarian Foundation Model initiative is to also develop and build more radical ideas (besides catching up). Within this, I'm stoked to be involved in an exciting project on tokenizer-free FoMos with @vjhofmann 👇
📢 We're hiring a PhD student in tokenizer-free foundation models! The position will have a double affiliation with @LMU_Muenchen and @utn_nuremberg, co-supervised by @y_m_asano and me. Come work with us in Munich and Nuremberg! 👇
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FunAI retweeted
Happening Now! Come to VGI workshop @CVPR in Room 703 to listen to the excellent keynote speakers: Robert Geirhos @GoogleDeepMind; @AdtRaghunathan @CSDatCMU; @mattdeitke @Meta; @y_m_asano @funailab; @alexgkendall @wayve_ai; Andrea Vedaldi; Alexei Efros; Kristen Grauman @CVPRConf
Checkout our @CVPR VGI workshop on 3rd Jun 2026 cvpr2026-vgi-workshop.limitl… in Room 703, Led by @HirokatuKataoka with Yoshihiro Fukuhara, @YonglongT, @elliottszwu, Ryousuke Yamada, @jianyuan_wang, Kohsuke Ide, @xianzhengoxford, @Koichi_N_, @yimiche @Oxford_VGG! @CVPRConf #CVPR2026!!
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FunAI retweeted
Looking forward to speaking here at ~11:30 room 703. Spoiler slide below 👇
Checkout our @CVPR VGI workshop on 3rd Jun 2026 cvpr2026-vgi-workshop.limitl… in Room 703, Led by @HirokatuKataoka with Yoshihiro Fukuhara, @YonglongT, @elliottszwu, Ryousuke Yamada, @jianyuan_wang, Kohsuke Ide, @xianzhengoxford, @Koichi_N_, @yimiche @Oxford_VGG! @CVPRConf #CVPR2026!!
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FunAI retweeted
[new CVPR'26 paper] 🔄 SSL works great when you have tons of data. But in 3D… we don’t. High-quality 3D scans are expensive, slow, and hard to scale. So what if we could pretrain 3D models without any real 3D scans? 1/
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FunAI retweeted
Group picture of our @ELLISforEurope @Ellis_Amsterdam Foundation Model PhD school! 👏 🎉 @CSProfKGD @cgmsnoek @robrombach @FrankRHutter @YGandelsman @eliricci_ @nuriaoliver @sainingxie @PascalMettes, @KatiaShutova Hinrich Schütze, Robert Geirhos
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Spending the day in Nuremberg with @y_m_asano and his group ❤️ Missing the bus is not going to deter us, the talk must go on! 🤓
My slide deck is feature complete. Finally ready for my European speaking tour 🇪🇺 Plan to record this talk too, once back in my #Toronto home studio.
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Happy to share what we've been cooking! 🎊🎊 Our next iteration of the ELLIS PhD school is set to be an *absolutely amazing* one with this stellar lineup of speakers. ..And we even have some more speakers to be confirmed. 👀 If you haven't yet, go apply :)
🚀 Two Big Announcements for ELLIS | ELIAS | ELLIOT Winter School on Foundation Models (FoMo) 2026, which is organised at the Tolhuistuin from 24-27 March 2026! 1️⃣ We’re excited to reveal the incredible speaker lineup for FoMo 2026... (1)
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Replying to @FunAILab
@FunAILab + CVMP Lab of @EddyIlg retreat: ☑. From mountains to hackathon to good food, we've had some intense but good days with lots of new ideas 🎉.
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Now finally accepted at @emnlpmeeting! I think the technique and high-level ideas i) allow bidirectional attention for prompt & ii) (maybe) process input-query differently from answer generation will stick around.
Today we introduce Bidirectional Instruction Tuning (Bitune). It's a new way of adapting LLMs for the instruction->answering stage. It allows the model to process the instruction/question with bidirectional attention, while the answer generation remains causal.
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Today we release Franca, a new vision Foundation Model that matches and sometimes outperforms DINOv2. The data, the training code and the model weights (with intermediate checkpoints) are open-source, allowing everyone to build on this. Methodologically, we introduce two new SSL components, one is a multi-granularity SK clustering loss that utilizes Matryoshka representations and a quick post-pretraining scheme to remove unwanted spatial biases. This is the result of a close and fun collaboration @valeoai (in France) and @FunAILab (in Franconia)
Can open-data models beat DINOv2? Today we release Franca, a fully open-sourced vision foundation model. Franca with ViT-G backbone matches (and often beats) proprietary models like SigLIPv2, CLIP, DINOv2 on various benchmarks setting a new standard for open-source research🧵
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Hello FunAI Lab at UTN 👋 I’m excited to start a new chapter of my research journey here in Nuremberg as a visiting postdoc. Excited for inspiring collaborations and impactful research ahead with @y_m_asano and the amazing students😀
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LoRA et al. enable personalised model generation and serving, which is crucial as finetuned models still outperform general ones in many tasks. However, serving a base model with many LoRAs is very inefficient! Now, there's a better way: enter Prompt Generation Networks, presented today @BMVCconf
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Is the community trying to surprise us today? 🤯 Because these benchmark-related papers from different research labs all dropped on the Daily Papers page at once! 🎉📑hf.co/papers ✨ LOKI: A Comprehensive Synthetic Data Detection Benchmark using Large Multimodal Models by Opendata lab ✨ MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models by @richardxp888 ✨ MEGA-Bench: Scaling Multimodal Evaluation to over 500 Real-World Tasks by the TigerLab ✨ LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content by @TelAvivUni @IBMResearch ✨ Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models by @PKU1898 @AlibabaGroup ✨ TemporalBench: Benchmarking Fine-grained Temporal Understanding for Multimodal Video Models by @MuCai7 ✨ LongMemEval: Benchmarking Chat Assistants on Long-Term Interactive Memory by @DiWu0162 @TencentGlobal ✨ TVBench: Redesigning Video-Language Evaluation by @FunAILab @_akhaliq
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