Can models understand each other's reasoning? 🤔

When Model A explains its Chain-of-Thought (CoT) , do Models B, C, and D interpret it the same way?

Our new preprint with @davidbau.bsky.social and @csinva.bsky.social explores CoT generalizability 🧵👇

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Eric’s setting is a really cool way of studying “pure” in-context learning, where symbols always mean different things in different contexts (so the model has to constantly do ICL). He has some really cool experiments you should check out 🔎

I just finished writing a blog post about a fake ICLR paper that caused a stir about a month ago. I think it has interesting implications for whether AI-generated text is "meaningful" or not.

sfeucht.github.io/rerereading/

I'm headed to San Diego this afternoon to attend the mech interp workshop at #NeurIPS! Really excited to give a lightning talk and catch up with everyone. 🌴

Looking forward to attending #cogsci2025 (Jul 29 - Aug 3)! I’m especially excited to meet students who will be applying to PhD programs in Computational Ling/CogSci in the coming cycle.

Please reach out if you want to meet up and chat! Email is the best way, but DM also works if you must!

quick🧵:

We've added a quick new section to this paper, which was just accepted to @COLM_conf! By summing weights of concept induction heads, we created a "concept lens" that lets you read out semantic information in a model's hidden states. 🔎

🚨 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...

Nikhil's recent paper is a tour de force in causal analysis! They show that LLMs keep track of what characters know in a story using "pointer" mechanisms. Definitely worth checking out.

I used to think formal reasoning was central to language and intelligence, but now I’m not so sure. Wrote a short post about my thoughts on this, with a couple chewy anecdotes. Would love to get some feedback or pointers to further reading.
sfeucht.github.io/syllogisms/

I'll present a poster for this work at NENLP tomorrow! Come find me at poster #80...

[📄] 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.

I'm searching for some comp/ling experts to provide a precise definition of “slop” as it refers to text (see: corp.oup.com/word-of-the-...)

I put together a google form that should take no longer than 10 minutes to complete: forms.gle/oWxsCScW3dJU...
If you can help, I'd appreciate your input! 🙏

I like this work a lot. Racism+misogyny in medicine is genuinely dangerous, so it's really important to keep tabs on model biases if we're going to use LLMs in clinical settings. It's nice to see that interpretability techniques are useful here.

Do you have a great experiment that you want to run on Llama 405b but not enough GPUs?

🚨 #NDIF is opening up more spots in our 405b pilot program! Apply now for a chance to conduct your own groundbreaking experiments on the 405b model. Details: 🧵⬇️

yes, this is what mechanistic interpretability research looks like