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Fantastic new work by John (Yueh-Han) Chen (with Brenden Lake and me trying not to cause too much trouble). We study systematic generalization in a safety setting and find LLMs struggle to consistently respond safely when we vary how we ask naive questions. More fun analyses in the paper!

Our paper Prisma: An Open Source Toolkit for Mechanistic Interpretability in Vision and Video received an Oral at the Mechanistic Interpretability for Vision Workshop at CVPR 2025! 🎉 We’ll be in Nashville next week. Come say hi 👋 #CVPR2025 Mechanistic Interpretability for Vision @ CVPR2025

You (yes, you!) should work with Sydney! Either short-term this summer, or longer term at her nascent lab at NYU!

Today! Come hear from some wonderful folks about problem solving and design at 1 PM PT / 4 PM ET / 8 PM UTC

How would you make an LLM "forget" the concept of dog — or any other arbitrary concept? 🐶❓ We introduce SAMD & SAMI — a novel, concept-agnostic approach to identify and manipulate attention modules in transformers.

Cool new work on localizing and removing concepts using attention heads from colleagues at NYU and Meta!

John has some nice new results showing that some frontier models do worse on our safety benchmark than their predecessors. Take a look!

We've been using smile to develop behavioral web experiments in the lab for the last year+. Everything from the simplest survey-like judgment collections to complex game-like designs (e.g., exps.gureckislab.org/e/laugh-melted…) is easier to develop and deploy. Consider it for your next exp!