Co-lead with Lea-Maria Schmitt, @emincelik , and with Floris P. de Lange, and @mtoneva1 💫. We had a lot of fun discussing and writing this paper together :). We'd love to hear your feedback!
1/5 Over a decade of comparing deep neural networks to the human brain—but what have we actually learned? Our new @TrendsCognSci Feature Review synthesizes a decade of brain–DNN comparisons, asking what they reveal about brain function across vision and language.
5/5 Looking ahead, we hope this synthesis helps shape the next decade of research through deeper cross-modal insights, brain data-driven improvements to DNNs, and model-driven neuroscience experimentation. Read the full review with Open Access:
https://t.co/i87pJ2CmgJ
4/5 As the field enters its second decade, we argue that combining constructive (building models) and deconstructive (interpreting models) approaches can move brain–DNN comparisons from descriptive alignment toward a theory-constraining scientific tool.
3/5 We organize findings along three shared dimensions—representations, architectures, and objectives—highlighting where DNNs have validated long-standing neuroscientific hypotheses, where they've generated new ones, and where findings from vision and language converge or diverge
@TrendsCognSci 2/5 Why bring vision and language together? Although both address closely related problems, research has largely evolved in parallel across the two fields. Bringing them together reveals shared computational principles—and where each is shaped by its own unique constraints.
Good morning #ICLR2026 ☀️
The Re-Align workshop kicks off in 30 minutes! A full day on what we can actually do with representational alignment, from brains to language models to agents.
Schedule in the thread 👇
I'm excited to be giving an invited talk at the #iclr2026 Re-Align workshop, talking about how we can improve precise instruction following generalization:
9:15 AM Rio time, Monday, April 27
https://t.co/OC7lF6XgJe
Very excited to have been awarded a Google PhD fellowship in NLP for my work on mechanistic interpretability! Big thanks to @Googleorg for the support, as well as to my supervisors @sandropezzelle@boknilev and @ELLISforEurope for all the help along the way.
@mntssys and I are excited to announce circuit-tracer, a library that makes circuit-finding simple!
Just type in a sentence, and get out a circuit showing (some of) the features your model uses to predict the next token. Try it on @neuronpedia: https://t.co/JYmcZz1f1J
🔄✨ Come join us at the Second edition of the Re-Align workshop @iclr_conf! 🚀🧠 The workshop explores the fascinating question of how artificial and biological systems align in their representations of the world. #ReAlign#ICLR2025
🚨Call for Papers🚨
The Re-Align Workshop is coming back to #ICLR2025
Our CfP is finally up! Come share your representational alignment work at our interdisciplinary workshop at
@iclr_conf
https://t.co/taAxgAwaT1
So so happy to have @__init_self speaking about her cool work in person! We had a blast with all the questions and discussions! Can’t wait to hear more about the awesome CorText 🤖 🔥!
1/n🤖🧠 New paper alert!📢 In "Assessing Episodic Memory in LLMs with Sequence Order Recall Tasks" (https://t.co/S8BZzkFVM6) we introduce SORT as the first method to evaluate episodic memory in large language models. Read on to find out what we discovered!🧵