🎉 Presenting at #ICML2025 tomorrow! Come and explore how representational similarities behave across datasets :) 📅 Thu Jul 17, 11 AM-1:30 PM PDT 📍 East Exhibition Hall A-B #E-2510 Huge thanks to @lorenzlinhardt.bsky.social, Marco Morik, Jonas Dippel, Simon Kornblith, and @lukasmut.bsky.social!

Laure Ciernik@lciernik.bsky.social · last yr.

If two models are more similar to each other than a third on ImageNet, will this hold for medical/satellite images? Our #icml2025 paper analyses how vision model similarities generalize across datasets, the factors that influence them, and their link to downstream task behavior. 🧵1/7

🚨 Poster at #ICML2025! How can LLMs really keep up with the world? Come by E-2405 on July 15th (4:30–7:00pm) to check out WikiBigEdit – our new benchmark to test lifelong knowledge editing in LLMs at scale. 🔗 Real-world updates 📈 500k+ QA edits 🧠 Editing vs. RAG vs. CL

🧠🤖 We’re hiring a Postdoc in NeuroAI! Join CRC1233 "Robust Vision" (Uni Tübingen) to build benchmarks & evaluation methods for vision models, bridging brain & AI. Work with top faculty & shape vision research. Apply: tinyurl.com/3jtb4an6 #NeuroAI #Jobs

📢 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! 🏁🌟

🚨 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.

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! 🌟

🧠 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. 👇

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😉

🚨 New paper alert! 🚨 We’ve just launched openretina, an open-source framework for collaborative retina modeling across datasets and species. A 🧵👇 (1/9)

CuratedThoughts: Data Curation for RL Datasets 🚀 Since DeepSeek-R1 introduced reasoning-based RL, datasets like Open-R1 & OpenThoughts emerged for fine-tuning & GRPO. Our deep dive found major flaws — 25% of OpenThoughts needed elimination by data curation. Here's why 👇🧵

🔥 #CVPR2025 Submit your cool papers to Workshop on Emergent Visual Abilities and Limits of Foundation Models 📷📷🧠🚀✨ sites.google.com/view/eval-fo... Submission Deadline: March 12th!

EVAL-FoMo 2

A Vision workshop on Evaluations and Analysis

sites.google.com

🚀 We’re hiring! Join Bernhard Schölkopf & me at @ellisinsttue.bsky.social to push the frontier of #AI in education! We’re building cutting-edge, open-source AI tutoring models for high-quality, adaptive learning for all pupils with support from the Hector Foundation. 👉 forms.gle/sxvXbJhZSccr...

🚨Great Models Think Alike and this Undermines AI Oversight🚨 New paper quantifies LM similarity (1) LLM-as-a-judge favor more similar models🤥 (2) Complementary knowledge benefits Weak-to-Strong Generalization☯️ (3) More capable models have more correlated failures 📈🙀 🧵👇

Our EML team has 4 #ICLR25 Papers accepted! I am proud of my students and grateful to be a part of many successful collaborations. More details will appear on our website (www.eml-munich.de) but here are the snapshots.

📄 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! 🧵

How to Merge Your Multimodal Models Over Time?

Model merging combines multiple expert models - finetuned from a base foundation model on diverse tasks and domains - into a single, more capable model. However, most existing model merging approaches...

arxiv.org

🚨Looking to test your foundation model on an arbitrary and open-ended set of capabilities, not explicitly captured by static benchmarks? 🚨 Check out ✨ONEBench✨, where we show how sample-level evaluation is the solution. 🔎 arxiv.org/abs/2412.06745

🤔 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:

🚀New Paper: Active Data Curation Effectively Distills Multimodal Models arxiv.org/abs/2411.18674 Smol models are all the rage these days & knowledge distillation (KD) is key for model compression! We show how data curation can effectively distill to yield SoTA FLOP-efficient {C/Sig}LIPs!! 🧵👇