🎓PhD application season is back! We’re hiring ONLY through the ELLIS @ellis.eu and the MCML @munichcenterml.bsky.social 📌Please denote Prof. Zeynep Akata @zeynepakata.bsky.social as your preferred supervisor! 👉 Link to ELLIS (ellis.eu/news/ellis-p...) and MCML (mcml.ai/opportunitie...)

Are you at #ICCV2025? 🎉 @iccv.bsky.social EML Munich is presenting two poster papers—come say hi to our authors! Details in the thread 👇

🔥We celebrate 3 papers accepted to NeurIPS 2025, see you in San Diego! 🥳Topics include diffusion models, sparse autoencoders (SAEs) and neural chunking. See the thread for highlights👇

🎓PhD Spotlight: Karsten Roth Celebrate @confusezius.bsky.social , who defended his PhD on June 24th summa cum laude! 🏁 His next stop: Google DeepMind in Zurich! Join us in celebrating Karsten's achievements and wishing him the best for his future endeavors! 🥳

This project was a collaboration between @eml-munich.bsky.social and Huawei Paris Noah’s Ark Lab. Thank you to my collaborators @qbouniot.bsky.social, Vasilii Feofanov, Ievgen Redko, and particularly to my advisor @zeynepakata.bsky.social for guiding me through my first PhD project!

🎓PhD Spotlight: Shyamgopal Karthik Celebrate @shyamgopal.bsky.social , who will defend his PhD on 23rd June! Shyam has been a PhD student @unituebingen.bsky.social since October 2021, supervised by @zeynepakata.bsky.social.

Join us in taking stock of the state of the field of explainability in computer vision, at our Workshop on Explainable Computer Vision: Quo Vadis? at #ICCV2025! @iccv.bsky.social

📢 Landed in Nashville🎺 for #CVPR2025! The EML group is presenting 4 exciting papers — come say hi at our poster sessions! More details in the thread — see you there! 🏁🌟

🎓PhD Spotlight: Leonard Salewski Celebrate @l-salewski.bsky.social, who will defend his PhD on 24th June! 📸🎉

🎓PhD Spotlight: Thomas Hummel A spotlight on our one and only @hummelth.bsky.social , who will defend his PhD on 23rd June! 🎉 Thomas started his PhD in 2020 at ‪‪@unituebingen.bsky.social as part of the IMPRS-IS program under the supervision of @zeynepakata.bsky.social . 👇 His full story:

🚨 Happy to announce that one paper, "Understanding the Limits of Lifelong Knowledge Editing in LLMs", is accepted at #icml2025 ! Congrats to @lukasthede.bsky.social , @confusezius.bsky.social , Matthias Bethge, @zeynepakata.bsky.social , and @tomhartvigsen.bsky.social . 👇 Highlights in the thread

🎓PhD Spotlight: Jae Myung Kim We’re thrilled to celebrate Jae Myung Kim, who will defend his PhD on 25th June! 🎉 Jae Myung began his PhD at @unituebingen.bsky.social as part of the ELLIS & IMPRS-IS programs, advised by @zeynepakata.bsky.social and collaborating closely with Cordelia Schmid.

#CVPR2025 is heading to the 'Music City' — Nashville! 🎺 Join us from June 11–15. We're thrilled to announce that we'll be presenting four papers at @cvprconference.bsky.social! Check out the thread below for highlights, and feel free to stop by and chat with our authors! 📷👇

We’ve landed in Singapore for #ICLR2025! The EML group is presenting 4 exciting papers — come say hi at our poster sessions! 👇Let's chat! More details in the thread — see you there! 🌟

🎓 PhD Spotlight: Otniel-Bogdan Mercea We’re excited to celebrate @merceaotniel.bsky.social , who will defend his PhD on April 16th! See the thread to feature his research highlights👇

9/ 📘 Want to test your method at scale? 📄 Paper: arxiv.org/abs/2503.05683 🗂️ Benchmark: huggingface.co/datasets/luk... 💻 Code: github.com/ExplainableM... Let’s build LLMs that truly stay up to date. 🔄 Excited to see what the community does with this!

2/ 📣 Introducing WikiBigEdit: a new benchmark for lifelong knowledge editing. It includes: 📌 500K+ real-world QA pairs based on Wikidata 📆 8 time steps over 6 months (Feb–Jul 2024) and continuously updatable 🧪 Rich evaluations: reasoning, generalization, locality, …

🧠 Keeping LLMs factually up to date is a common motivation for knowledge editing. But what would it actually take to support this in practice at the scale and speed the real world demands? We explore this question and really push the limits of lifelong knowledge editing in the wild. 👇

🌍 #ICLR2025 is coming to the beautiful city of Singapore — April 24–28! We're excited to share 4 upcoming papers being presented at the conference. Check out the thread for highlights, and come chat with the authors if you're interested! 🧵👇

Thrilled to announce that four papers from our group have been accepted to #CVPR2025 in Nashville! 🎉 Congrats to all authors & collaborators. Our work spans multimodal pre-training, model merging, and more. 📄 Papers & codes: eml-munich.de#publications See threads for highlights in each paper. #CVPR

Happy to share that we have 4 papers to be presented in the coming #ICLR2025 in the beautiful city of #Singapore . Check out our website for more details: eml-munich.de/publications. We will introduce the talented authors with their papers very soon, stay tuned😉

Can we enhance the performance of T2I models without any fine-tuning? We show that with our ReNO, Reward-based Noise Optimization, one-step models consistently surpass the performance of all current open-source Text-to-Image models within the computational budget of 20-50 sec! #NeurIPS2024

📄 New Paper: "How to Merge Your Multimodal Models Over Time?" arxiv.org/abs/2412.06712 Model merging assumes all finetuned models are available at once. But what if they need to be created over time? We study Temporal Model Merging through the TIME framework to find out! 🧵

😵‍💫 Continually pretraining large multimodal models to keep them up-to-date all-the-time is tough, covering everything from adapters, merging, meta-scheduling to data design and more! So I'm really happy to present our large-scale study at #NeurIPS2024! Come drop by to talk about all that and more!

After a break of over 2 years, I'm attending a conference again! Excited to attend NeurIPS, even more so to be presenting ReNO, getting inference-time scaling and preference optimization to work for text-to-image generation. Do reach out if you'd like to chat!

🤔 Can you turn your vision-language model from a great zero-shot model into a great-at-any-shot generalist? Turns out you can, and here is how: arxiv.org/abs/2411.15099 Really excited to this work on multimodal pretraining for my first bluesky entry! 🧵 A short and hopefully informative thread: