🚨 New Paper!! How can we train LLMs using 100M words? In our babyLM paper, we introduce a new self-synthesis training recipe to tackle this question! 🍼💻 This was a fun project co-led by me, Yingtian Tang, Abdulkadir Gokce, w/ Hannes Mehrer & Martin Schrimpf 🧵⬇️

🚨 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/ Greta Tuckute, Antoine Bosselut, & Martin Schrimpf 🧵👇

🚨 New Preprint!! LLMs trained on next-word prediction (NWP) show high alignment with brain recordings. But what drives this alignment—linguistic structure or world knowledge? And how does this alignment evolve during training? Our new paper explores these questions. 👇🧵

AI vision is insanely good nowadays—but is it really like human vision or something else entirely? In our new pre-print, we pinpoint a fundamental visual mechanism that's trivial for humans yet causes most models to fail spectacularly. Let's dive in👇🧠 [arxiv.org/abs/2504.05253]

🚨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/ 🧵👇

🧠 NEW PREPRINT Many-Two-One: Diverse Representations Across Visual Pathways Emerge from A Single Objective biorxiv.org/content/10.110…

🧠 New preprint: we show that model-guided microstimulation can steer monkey visual behavior. Paper: arxiv.org/abs/2510.03684 🧵