This week three new researchers joined the Mistral Warsaw office :). Let's achieve great things :).
Good luck @danie1marczak, @MozejkoMarcin, @f_szatkowski.
On the funny side, this means 75% monthly growth. Stay tuned for more good news soon.
Liner is partnering with @spoticlr at #ICLR2026 — supporting Best Paper and Travel Awards for LLM research.
And to celebrate, we're giving away:
✈️ Round-trip flights + hotel to #ICML2026 in Seoul
🎁 $300 Liner Credits
Follow @search_liner + repost to enter by 4/27.
Liner is built for research workflows. Find papers, verify sources, and write with citations in one place.
See you in 🇧🇷 and 🇰🇷!
@iclr_conf@icmlconf
🇧🇷 Bom dia @iclr_conf ! This evening, together with @f_szatkowski, we’re presenting our paper “Universal Properties of Activation Sparsity in Modern Large Language Models”. Stop by Poster 912 in Pavilion 3 and let’s have a chat.
We are presenting "Universal Properties of Activation Sparsity in Modern Large Language Models" at ICLR 2026!
We ask a simple question: how sparse are modern LLMs, really — and does it matter? 👇
6/ Takeaway: activation sparsity isn't just a ReLU-era trick. It's a structural property of modern LLMs that scales favorably — and our work provides a principled way to harness it for efficiency and acceleration.
1/7 If Andrew Ng is right that the LR is the most important ML hyperparam, it's got some competition! We show that the softmax temperature is a game-changer in crafting NN representations. Often overlooked, it quietly governs generalization, collapse, and compression. A thread 👇
🚨We’re thrilled to present our paper “CDI: Copyrighted Data Identification in #DiffusionModels” at #CVPR2025 in Nashville! 🎸❗️
"Was this diffusion model trained on my dataset?"
Learn how to find out:
📍 Poster #276
🗓️ Saturday, June 14
🕒 3:00 – 5:00 PM PDT
📜https://t.co/CLUrBtmQrI
TL;DR: We show that Membership Inference Attacks (MIAs) struggle to detect training data in SOTA Diffusion Models (DMs) and instead propose the first dataset inference method to achieve this goal.
#AI #MachineLearning #GenerativeAI #Copyright
🚨Scaling RL
Most RL methods’ performance saturate at ~5 layers. In this work led by @kevin_wang3290, we crack the right configuration for scaling Contrastive RL and go beyond 1000 layers NNs! Deep NNs unlock emergent behaviors and other cool properties. Check out Kevin’s thread!
📢You’re invited to the Machine Learning Summer School on Drug and Materials Discovery (MLSS^D 2025)! 🚀🔬
🌟 MLSS^D is an intensive summer school focused on cutting-edge machine learning techniques and their applications in drug discovery and materials science.
By joining MLSS^D, you will:
✅ Learn from leading experts in ML and computational sciences
✅ Explore real-world case studies and practical applications
✅ Share your research with the world during a poster session
✅ Connect with researchers and professionals from around the world
🔗 Registration is now open! Register now: https://t.co/Epx27THRLt
🔥 When? July 1–6, 2025
📍 Where? Kraków, Poland
🌐 Find out more on our website: https://t.co/iPKCk04XOG
🚀 Don’t miss this unique opportunity to expand your knowledge and network in one of Europe’s most beautiful cities!
#MLSSD2025 #MachineLearning #DrugDiscovery #MaterialsScience #MLinPL
We are presenting "Exploiting Activation Sparsity with Dense to Dynamic-k Mixture-of-Experts Conversion" together with Bartosz Wójcik and @AjPiorczynski today at #NeurIPS2024 ! 🎉 If you are around and want to chat about efficiency, stop by poster 2304 at session 6 east at 4:30!