Anthropic dropped some insights into how AI brains work with their circuit tracing method. Turns out LLMs are bad at math because they’re eyeballing it (“36+59? Eh, 40ish+60ish=95?”). It means we’re one step closer to understanding the inner workings of LLMs. #LLMs #AI #Interpretability

*Automatically Interpreting Millions of Features in LLMs* by @norabelrose.bsky.social et al. An open-source pipeline for finding interpretable features in LLMs with sparse autoencoders and automated explainability methods from @eleutherai.bsky.social. arxiv.org/abs/2410.13928

Explainable and Interpretable Multimodal Large Language Models: A Comprehensive Survey Presents a framework categorizing MLLM explainability across data, model, and training perspectives to enhance transparency and trustworthiness. 📝 arxiv.org/abs/2412.02104

I am extremely honoured to receive the @ERC_Research #ERCCoG award for #RUNES. For the next five years, I will be working on the mathematical, computational, and experimental (!!) sides to understand how higher-order interactions change how we think and coordinate.

Latest one out! 👇👇👇👇👇

Check out our poster at #LoG2024, based on our #TMLR paper: 📍 “A True-to-the-Model Axiomatic Benchmark for Graph-based Explainers” 🗓️ Tuesday 4–6 PM CET 📌 Poster Session 2, GatherTown Join us to discuss graph ML explainability and benchmarks #ExplainableAI #GraphML openreview.net/forum?id=HSQTv3R8Iz

🌟🤖📝 **Boosting human competences with interpretable and explainable artificial intelligence** How can AI *boost* human decision-making instead of replacing it? We talk about this in our new paper. doi.org/10.1037/dec0... #AI #XAI #InterpretableAI #IAI #boosting #competences 🧵👇

NeurIPS Conference is now Live on Bluesky! -NeurIPS2024 Communication Chairs

Even as an interpretable ML researcher, I wasn't sure what to make of Mechanistic Interpretability, which seemed to come out of nowhere not too long ago. But then I found the paper "Mechanistic?" by @nsaphra.bsky.social and @sarah-nlp.bsky.social, which clarified things.

18M + 1. 💙, Mar🐫

ICLR is a top AI conference, and while the 2025 papers aren’t officially out yet, reviews are open. I’m diving into the highest rated in Interpretability and Explainable AI. Interestingly, the top ones focus on Mechanistic Interpretability, a promising topic that our team is starting to explore.

For Science Magazine, I wrote about "The Metaphors of Artificial Intelligence". The way you conceptualize AI systems affects how you interact with them, do science on them, and create policy and apply laws to them. Hope you will check it out! www.science.org/doi/full/10....

Bluesky feels like traveling back to the golden age of Twitter: when the follow button meant something, and your feed wasn’t a dystopian lineup of blue-tagged bots. It’s refreshing to be somewhere I don’t need an AI to explain why I’m seeing a post. Let’s hope we don’t ruin it this time!