LLMs can retrieve knowledge — but can they connect it in *creative* ways to solve problems? Introducing CresOWLve 🦉, a new benchmark that evaluates creative problem-solving over real-world knowledge, using puzzles that require multiple creative thinking strategies.👇

1/ 🌍 How does mixing data from hundreds of languages affect LLM training? In our new paper "Revisiting Multilingual Data Mixtures in Language Model Pretraining" we revisit core assumptions about multilinguality using 1.1B-3B models trained on up to 400 languages. 🧵👇

🎤 Prof. Iryna Gurevych, Distinguished Professor at the National Center for Cybersecurity @athenecenter.bsky.social and Director of the UKP Lab at @tuda.bsky.social, delivered a keynote on “How to Make AI-Native Internet Content Secure? Coping with Synthetic and Misleading Data.”

🎉 Congratulations to Assistant Professors @abosselut.bsky.social (IC), @bunnech.bsky.social (IC & SV), and @mschrimpf.bsky.social (IC & SV) for being selected as #AI2050 Early Career Fellows by @schmidtsciences.bsky.social ! 🔗 Full article: actu.epfl.ch/news/epfl-pr...

Recruiting PhDs & postdocs for: 🤖 agents "taking over" science (hypogenic.ai and 📌) 🧪 Real scientists ➡️AI (e.g., materials, chem, physics) 📜 Theory + incentives for H-AI collab & credit (e.g., formalizing tacit knowledge) new adventures for me, 🔄 if you can! 🙌 chenhaot.com/recruiting.h...

If you're interested in doing a postdoc at @icepfl.bsky.social , there's still time to apply for the @epfl-ai-center.bsky.social postdoctoral fellowships. Apart from this, I'm also recruiting postdocs in developing novel training algorithms for reasoning models and agentic AI.

Join us again at #MELT workshop (520D) at #COLM2025 to hear from @ImanolSchlag about #Apertus, the largest multilingual LLM trained on over 1000 languages.

Kicking off #MELT workshop at #COLM2025 with Monojit Choudhury talking about "Meta-Cultural Competence: What LLMs Should Know About Culture to Serve the Next Billion Users" !

Come join us in 520D (all the way down the hall and around the corner) at #COLM2025 for the first workshop on multilingual and equitable language technologies!

Very happy this paper got accepted to NeurIPS 2025 as a Spotlight! 😁 Main takeaway: In mechanistic interpretability, we need assumptions about how DNNs encode concepts in their representations (eg, the linear representation hypothesis). Without them, we can claim any DNN implements any algorithm!

Tiago Pimentel@tpimentel.bsky.social · last yr.

Mechanistic interpretability often relies on *interventions* to study how DNNs work. Are these interventions enough to guarantee the features we find are not spurious? No!⚠️ In our new paper, we show many mech int methods implicitly rely on the linear representation hypothesis🧵

What's the right unit of analysis for understanding LLM internals? We explore in our mech interp survey (a major update from our 2024 ms). We’ve added more recent work and more immediately actionable directions for future work. Now published in Computational Linguistics!

1/🚨 New preprint How do #LLMs’ inner features change as they train? Using #crosscoders + a new causal metric, we map when features appear, strengthen, or fade across checkpoints—opening a new lens on training dynamics beyond loss curves & benchmarks. #interpretability

💡Can we optimize LLMs to be more creative? Introducing Creative Preference Optimization (CrPO) and MuCE (Multi-task Creativity Evaluation Dataset). Result: More novel, diverse, surprising text—without losing quality! 📝 Appearing at #EMNLP2025

The next generation of open LLMs should be inclusive, compliant, and multilingual by design. That’s why we @icepfl.bsky.social @ethz.ch @cscsch.bsky.social ) built Apertus.

EPFL School of Computer and Communication Sciences@icepfl.bsky.social · 11mo ago

EPFL, ETH Zurich & CSCS just released Apertus, Switzerland’s first fully open-source large language model. Trained on 15T tokens in 1,000+ languages, it’s built for transparency, responsibility & the public good. Read more: actu.epfl.ch/news/apertus...

EPFL, @ethz.ch and the @cscsch.bsky.social released Apertus today, Switzerland’s first large-scale, open, multilingual language model — a milestone in generative AI for transparency and diversity. Find out more here: ai.epfl.ch/apertus-a-fu... @abosselut.bsky.social @icepfl.bsky.social

Apertus: a fully open, transparent, multilingual language model - EPFL AI Center

EPFL, ETH Zurich and the Swiss National Supercomputing Centre (CSCS) released Apertus today, Switzerland’s first large-scale, open, multilingual language model — a milestone in generative AI for trans...

ai.epfl.ch

EPFL, ETH Zurich & CSCS just released Apertus, Switzerland’s first fully open-source large language model. Trained on 15T tokens in 1,000+ languages, it’s built for transparency, responsibility & the public good. Read more: actu.epfl.ch/news/apertus...

Very happy to see that Pleias multilingual data processing pipelines have contributed to the largest open pretraining project in Europe. From their tech report: huggingface.co/swiss-ai/Ape...

EPFL School of Computer and Communication Sciences@icepfl.bsky.social · 11mo ago

EPFL, ETH Zurich & CSCS just released Apertus, Switzerland’s first fully open-source large language model. Trained on 15T tokens in 1,000+ languages, it’s built for transparency, responsibility & the public good. Read more: actu.epfl.ch/news/apertus...

Die Schweiz steigt ins Rennen der grossen Sprachmodelle ein. Unter dem Namen #Apertus veröffentlichen @ethz.ch, @icepfl.bsky.social und das @cscsch.bsky.social das erste vollständig offene, mehrsprachige #LLM des Landes. Fürs MAZ habe ich Apertus kurz analysiert: www.maz.ch/news/apertus...

Apertus: ein neues Sprachmodell für die Schweiz

maz.ch

recently gave a talk on <Reality Checks> at two venues, and discussed (and rambled) about how leaderboard chasing is awesome (and we want it to continue) but that this isn't easy because everyone (me! me! me!) wants to write more papers. the link to the slide deck in the reply.

🚨New Preprint! In multilingual models, the same meaning can take far more tokens in some languages, penalizing users of underrepresented languages with worse performance and higher API costs. Our Parity-aware BPE algorithm is a step toward addressing this issue: 🧵

The EPFL NLP lab is looking to hire a postdoctoral researcher on the topic of designing, training, and evaluating multilingual LLMs: docs.google.com/document/d/1... Come join our dynamic group in beautiful Lausanne!

EPFL NLP Postdoctoral Scholar Posting - Swiss AI LLMs

The EPFL Natural Language Processing (NLP) lab is looking to hire a postdoctoral researcher candidate in the area of multilingual LLM design, training, and evaluation. This postdoctoral position is as...

docs.google.com

📣 Life update: Thrilled to announce that I’ll be starting as faculty at the Max Planck Institute for Software Systems this Fall! I’ll be recruiting PhD students in the upcoming cycle, as well as research interns throughout the year: lasharavichander.github.io/contact.html

EPFL and ETH Zürich are building together a Swiss made LLM from scratch. Fully open and multilingual, the model is trained on CSCS's supercomputer "Alps" and supports sovereign, transparent, and responsible AI in Switzerland and beyond. Read more here: ai.epfl.ch/a-language-m... #ResponsibleAI

A language model built for the public good     - EPFL AI Center

ETH Zurich and EPFL will release a large language model (LLM) developed on public infrastructure. Trained on the “Alps” supercomputer at the Swiss National Supercomputing Centre (CSCS), the new LLM ma...

ai.epfl.ch

Check out Silin's paper done in collaboration with Apple on reinforcing abstract thinking in reasoning traces!

@silingao.bsky.social · last yr.

NEW PAPER ALERT: Recent studies have shown that LLMs often lack robustness to distribution shifts in their reasoning. Our paper proposes a new method, AbstRaL, to augment LLMs’ reasoning robustness, by promoting their abstract thinking with granular reinforcement learning.

Check out @bkhmsi.bsky.social 's great work on mixture-of-expert models that are specialized to represent the behavior of known brain networks.

Badr AlKhamissi@bkhmsi.bsky.social · last yr.

🚨 New Preprint!! Thrilled to share with you our latest work: “Mixture of Cognitive Reasoners”, a modular transformer architecture inspired by the brain’s functional networks: language, logic, social reasoning, and world knowledge. 1/ 🧵👇

Many AI models speak dozens of languages, but do they grasp cultural context? 🗣️🌍 The INCLUDE benchmark from EPFL's NLP Lab and @cohereforai.bsky.social reveal that there is still a gap... 👉 Find out how benchmarks like INCLUDE can help make AI truly inclusive: actu.epfl.ch/news/beyond-...

Beyond translation – making AI multicultural

A team of international researchers led by EPFL developed a multilingual benchmark to determine Large Language Models ability to grasp cultural context.

actu.epfl.ch

I guess that now that I have 1% of my Twitter followers follow me here 😅, I should announce it here too for those of you no longer checking Twitter: my nonfiction book, "Lost in Automatic Translation" is coming out this July: lostinautomatictranslation.com. I'm very excited to share it with you!

Super excited to share that our paper "A Logical Fallacy-Informed Framework for Argument Generation" has received the Outstanding Paper Award 🎉🎉 at NAACL 2025! Paper: aclanthology.org/2025.naacl-l... Code: github.com/lucamouchel/... #NAACL2025

A Logical Fallacy-Informed Framework for Argument Generation

Luca Mouchel, Debjit Paul, Shaobo Cui, Robert West, Antoine Bosselut, Boi Faltings. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Lingu...

aclanthology.org

Antoine Bosselut@abosselut.bsky.social · last yr.

(NAACL) Luca and @debjit-paul.bsky.social's work looks at how we can guide LLMs to generate logically sound arguments. Introducing FIPO: a fallacy-informed framework that improves preference optimization to help LLMs avoid logical fallacies in argumentation.

Excited to be at #NAACL2025 in Albuquerque! I’ll be presenting our paper “The LLM Language Network” as an Oral tomorrow at 2:00 PM in Ballroom C, hope to see you there! Looking forward to all the discussions! 🎤 🧠

Using the 'right' data can hugely speed up LLM training, but how to find the best training data in the vast sea of a whole web crawl? We propose a simple classifier-based selection, enabling multilingual LLMs 🧵