Brains, Minds and Machines Summer Course 2025. Application deadline: Mar 24, 2025 mbl.edu/education/adva… See more information here: cbmm.mit.edu/summer-school/…

Want to scale models on brain datasets recorded with variable sensor layouts? Population Transformer at #ICLR2025 may be your answer! 🗺️ Fri, Apr 25 | 10am - 12:30pm (poster @ Hall 3 + Hall 2B #58) 🗣️ Fri, Apr 25 | 4:06 pm - 4:18 pm (oral @ Garnet 216-218) More ⬇️

Come find us in Hall 3! Can’t wait to meet you and talk about modeling brain data across heterogeneous datasets!

I'm so glad this paper finally lost the "release date procrastination" race against GTA6! 🥹

This paper is a bit heavy; however, the insights are good. The authors characterize the requirements for two representation to be similar. Also, there may be a connection with openreview.net/forum?id=yyYMA… (I should look into this). 🔗arxiv.org/abs/2506.03784

🚨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/ 🧵👇

PostDoc position (3.5y) available in interdisciplinary Collaborative Research Center "Common Ground". 🎯 Topic: Pragmatic reasoning about Common Ground 🎓 linguistics | philosophy of language | cognitive science 📅 Deadline: July 14 tinyurl.com/3vd9wa6p Please share!

A personal update. bhaskar-mitra.github.io/posts/2025/07/…

Uncertainty quantification (UQ) is key for safe, reliable LLMs... but are we evaluating it correctly? 🚨 Our ACL2025 paper finds a hidden flaw: if both UQ methods and correctness metrics are biased by the same factor (e.g., response length), evaluations get systematically skewed

I will be a SPAR mentor this Fall🤖 Check out the programme and apply by 20 August to work with me on formalising and/or measuring and/or intervening on goal-directed behaviour in AI agents More info on potential projects here 🧵

Our "Competitions of Mechanisms" paper proposes an interesting way to interpret LLM behaviors thru how it handles multiple conflicting mechanisms. E.G., in-context knowledge vs. in-weights knowledge🧐This is an elegant philophical way of thinking --

In our new paper, we explore how we can build encoding models that are both powerful and understandable. Our model uses an LLM to answer 35 questions about a sentence's content. The answers linearly contribute to our prediction of how the brain will respond to that sentence. 1/6

The Center for Brains, Minds & Machines [2013-2025]

LLMs as a synthesis between symbolic and distributed approaches to language 💯 arxiv.org/abs/2502.11856

Induction heads are surprisingly powerful. In a new preprint, we find that they can learn what to attend to in-context! We study this in a hierarchical prediction task and uncover a possible mechanism giving rise to in-context learning in induction heads. See thread for details!

New paper from my Meta internship! 🚀 We explored dual-architecture communication for latent reasoning in LLMs ☯️ —accepted at the #NeurIPS2025 Foundations of Reasoning in LLMs workshop. Paper: arxiv.org/pdf/2510.00494 1/9 🧵

I am hiring a PhD student to start my lab at UCL! Get in touch if you have any questions, the deadline to apply through ELLIS is 31 October. More details🧵

🚀 Excited to share LinEAS, our new activation steering method accepted at NeurIPS 2025! It approximates optimal transport maps e2e to precisely guide 🧭 activations achieving finer control 🎚️ with ✨ less than 32 ✨ prompts! 💻github.com/apple/ml-lineas 📄arxiv.org/abs/2503.10679