What's the right unit of analysis for understanding LLM internals? We explore in our mech interp survey (a major update from our 2024 ms).

We’ve added more recent work and more immediately actionable directions for future work. Now published in Computational Linguistics!

🚨 Registration is live! 🚨

The New England Mechanistic Interpretability (NEMI) Workshop is happening Aug 22nd 2025 at Northeastern University!

A chance for the mech interp community to nerd out on how models really work 🧠🤖

🌐 Info: nemiconf.github.io/summer25/
📝 Register: forms.gle/v4kJCweE3UUH...

[📄] Are LLMs mindless token-shifters, or do they build meaningful representations of language? We study how LLMs copy text in-context, and physically separate out two types of induction heads: token heads, which copy literal tokens, and concept heads, which copy word meanings.

The other key tasks are model search and benchmarking, with important applications like document generation and auditing.

Read more in our paper (with @davidbau.bsky.social
and Renée Miller) here: arxiv.org/abs/2403.02327

Excited to share that this is accepted to #EDBT2025! 🎉

🧵5/5

The second one is model versioning — where the aim is to map a model’s position within a lake of models, capturing these relationships using directed model graphs.

Other tasks, like model tree heritage recovery and differentiating outputs from various LLMs, are part of model versioning.

🧵4/5

We see four major tasks for Model Lakes.

The first is model attribution — tracing & understanding a model's output through attack techniques like model inversion (recovering user inputs) and interpretability methods like reverse engineering to analyze model behavior.

bsky.app/profile/srus...

🧵3/5

Model Lake is a system containing numerous heterogenous pre-trained models and related data in their natural formats. This concept is inspired from data lakes, which collect raw, unstructured data at scale.

By addressing shared challenges across research, we can unlock meaningful solutions. 👇

🧵2/5

🚀 How would you know what model to use? 🤗

With millions of models emerging rapidly, how do we verify, track, and find the right one?

We survey and formalize Model Lakes 🌊🤖 — a framework to structure, navigate, and make sense of this landscape.

Website: lakes.baulab.info

#AI #Database

🧵1/5

PhD Applicants: remember that the Northeastern Computer Science PhD application deadline is Dec 15.

It's a terrific time to do a PhD, with so many interesting things happening in AI.

Apply here:

www.khoury.northeastern.edu/apply/phd-ap...

More big news! Applications are open for the NDIF Summer Engineering Fellowship—an opportunity to work on cutting-edge AI research infrastructure this summer in Boston! 🚀