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Is encouraging LLMs to reason through a task always beneficial?🤔 NO🛑- inspired by when verbal thinking makes humans worse at tasks, we predict when CoT impairs LLMs & find 3 types of failure cases. In one OpenAI o1 preview accuracy drops 36.3% compared to GPT-4o zero-shot!😱

🚨 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. 👇🧵

If you’re at ICLR 2026 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!

EPFL researchers have discovered key ‘units’ in large AI models that seem to be important for language, mirroring the brain’s language system. When these specific units were turned off, the models got much worse at language tasks. #EPFL #AI #brain #communication #neuroscience

(1/11) Evolutionary biology offers powerful lens into Transformers learning dynamics! Two learning modes in Transformers (in-weights & in-context) mirror adaptive strategies in evolution. Crucially, environmental predictability shapes both systems similarly.

🚨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/ 🧵👇