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. 🧵👇

Keynote talk: Apertus: Democratizing Open and Compliant LLMs for Global Language Environments. Imanol Schlag introduces Apertus, a fully open suite of LLMs with a focus on compliance, transparency, and multilingual representation training across 1000+ languages. 🌍🤖

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

Proud to have been part of the team behind #Apertus 🌍✨ an open multilingual LLM. Trained on open data, supporting 1,800+ languages, and built with transparency, compliance & responsible AI in mind. 🤖 Try Apertus models: huggingface.co/collections/...

If you’re at @iclr-conf.bsky.social this week, come check out our spotlight poster INCLUDE during the Thursday 3:00–5:30pm session! I will be there to chat about all things multilingual & multicultural evaluation. Feel free to reach out anytime during the conference. I’d love to connect!

NEW PAPER ALERT: Generating visual narratives to illustrate textual stories remains an open challenge, due to the lack of knowledge to constrain faithful and self-consistent generations. Our #CVPR2025 paper proposes a new benchmark, VinaBench, to address this challenge.

Lots of great news out of the EPFL NLP lab these last few weeks. We'll be at @iclr-conf.bsky.social and @naaclmeeting.bsky.social in April / May to present some of our work in training dynamics, model representations, reasoning, and AI democratization. Come chat with us during the conference!

🚨 New Paper! Can neuroscience localizers uncover brain-like functional specializations in LLMs? 🧠🤖 Yes! We analyzed 18 LLMs and found units mirroring the brain's language, theory of mind, and multiple demand networks! w/ @gretatuckute.bsky.social, @abosselut.bsky.social, @mschrimpf.bsky.social 🧵👇

🚀 Introducing PICLe: a framework for in-context named-entity detection (NED) using pseudo-annotated demonstrations. 🎯 No human labeling needed—yet it outperforms few-shot learning with human annotations! #AI #NLProc #LLMs #ICL #NER

Introducing Global-MMLU🌍: A multilingual benchmark featuring MMLU translations in 42 languages crafted with: ✅ Human curation ✅ Extensive metadata ✅ Insights into cultural sensitivity Proud to have collaborated with Shivalika Singh, @sarahooker.bsky.social and Cohere For AI!

1/ 📘 Could ChatGPT get an engineering degree? Spoiler, yes! In our new @pnas.org article, we explore how AI assistants like GPT-4 perform in STEM university courses — and on average they pass a staggering 91.7% of core courses. 🧵 #AI #HigherEd #STEM #LLMs #NLProc

🚀 Introducing INCLUDE 🌍: A multilingual LLM evaluation benchmark spanning 44 languages! Contains *newly-collected* data, prioritizing *regional knowledge*. Setting the stage for truly global AI evaluation. Ready to see how your model measures up? #AI #Multilingual #LLM #NLProc

[email protected] is hiring for multiple positions in CS (including one open call): www.epfl.ch/about/workin... Apply to come join us in Beautiful Lausanne!