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Chris Wendler

@wendlerc.bsky.social
558 followers 444 following 36 posts

Postdoc at the interpretable deep learning lab at Northeastern University, deep learning, LLMs, mechanistic interpretability

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Chris Wendler @wendlerc.bsky.social · 24/02/2026
I am not very disciplined about syncing my bluesky and x account, if you are interested what I am up to please check out my x account x.com/wendlerch or website wendlerc.github.io
wendlerc.github.io
Chris Wendler
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Clément Dumas @butanium.bsky.social · 30/06/2025
Our mech interp ICML workshop paper got accepted to ACL 2025 main! 🎉 In this updated version, we extended our results to several models and showed they can actually generate good definitions of mean concept representations across languages.🧵
x.com
Clément Dumas on X: "Excited to share our latest paper, accepted as a spotlight at the #ICML2024 mechanistic interpretability workshop! We find evidence that LLMs use language-agnostic representations of concepts 🧵↘️ https://t.co/dDS5iv199i" / X
Excited to share our latest paper, accepted as a spotlight at the #ICML2024 mechanistic interpretability workshop! We find evidence that LLMs use language-agnostic representations of concepts 🧵↘️ https://t.co/dDS5iv199i
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Can @canrager.bsky.social · 13/06/2025
Can we uncover the list of topics a language model is censored on? Refused topics vary strongly among models. Claude-3.5 vs DeepSeek-R1 refusal patterns:
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Natalie Shapira @natalieshapira.bsky.social · 24/06/2025
I am really proud to share our work led by Nikhil Prakash and in collaboration with more mechanistic interpretability and Theory of Mind (ToM) researchers: arxiv.org/abs/2505.14685 You can find a tweet here with nice animations: x.com/nikhil07prak...
arxiv.org
Language Models use Lookbacks to Track Beliefs
How do language models (LMs) represent characters' beliefs, especially when those beliefs may differ from reality? This question lies at the heart of understanding the Theory of Mind (ToM) capabilitie...
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Chris Wendler @wendlerc.bsky.social · 08/04/2025
Check out Sheridan’s work on concept induction circuits -- the soft version of induction we were promised a while ago :) During our multilingual concept patching experiments I have always been wondering whether it is those circuits doing the work. Finally, some evidence:
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Chris Wendler @wendlerc.bsky.social · 21/03/2025
In case you ever wondered what you could do if you had SAEs for intermediate results of diffusion models, we trained SDXL Turbo SAEs on 4 blocks for you. We noticed that they specialize into a "composition", a "detail", and a "style" block. And one that is hard to make sense of.
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Chris Wendler @wendlerc.bsky.social · 18/03/2025
Apply to Akhil's lab, he is great!
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Aaron Mueller @amuuueller.bsky.social · 11/03/2025
Lots of work coming soon to @iclr-conf.bsky.social and @naaclmeeting.bsky.social in April/May! Come chat with us about new methods for interpreting and editing LLMs, multilingual concept representations, sentence processing mechanisms, and arithmetic reasoning. 🧵
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Andrew Lee @ajyl.bsky.social · 20/02/2025
Excited about recent reasoning models? What is happening under the hood? Join ARBOR: Analysis of Reasoning Behaviors thru *Open Research* - a radically open collaboration to reverse-engineer reasoning models! Learn more: arborproject.github.io 1/N
arborproject.github.io
ARBOR
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Chris Wendler @wendlerc.bsky.social · 17/02/2025
This seems like an elegant idea!
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David Bau @davidbau.bsky.social · 31/01/2025
DeepSeek R1 shows how important it is to be studying the internals of reasoning models. Try our code: Here @canrager.bsky.social shows a method for auditing AI bias by probing the internal monologue. dsthoughts.baulab.info I'd be interested in your thoughts.
dsthoughts.baulab
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Nathan Lambert @natolambert.bsky.social · 18/12/2024
The AI agent spectrum Separating different classes of AI agents from a long history of reinforcement learning. Why we can be optimistic for AI agents but also extremely critical of the terrible communications around them to date. Plus, some policy guidance.
buff.ly
The AI Agent Spectrum
Separating different classes of AI agents from a long history of reinforcement learning.
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Chris Wendler @wendlerc.bsky.social · 13/12/2024
The resources you find online on transformers are just next level... My jaw dropped when I first stumbled upon this video series: www.youtube.com/watch?v=V3NQ...
youtube.com
0L - Theory [rough early thoughts]
YouTube video by Mechanistic Interpretability
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Alexander Kolesnikov @handle.invalid · 04/12/2024
Ok, it is yesterdays news already, but good night sleep is important. After 7 amazing years at Google Brain/DM, I am joining OpenAI. Together with @xzhai.bsky.social and @giffmana.ai, we will establish OpenAI Zurich office. Proud of our past work and looking forward to the future.
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Chris Wendler @wendlerc.bsky.social · 25/11/2024
bit grumpy but great summary of the tokenformer paper www.youtube.com/watch?v=gfU5...
youtube.com
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters (Paper Explained)
YouTube video by Yannic Kilcher
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Julian Minder @jkminder.bsky.social · 22/11/2024
Can we understand and control how language models balance context and prior knowledge? Our latest paper shows it’s all about a 1D knob! 🎛️ arxiv.org/abs/2411.07404 Co-led with @kevdududu.bsky.social - @niklasstoehr.bsky.social , Giovanni Monea, @wendlerc.bsky.social, Robert West & Ryan Cotterell.
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Chris Wendler @wendlerc.bsky.social · 20/11/2024
In case you also wondered how to derive the maximal update parametrisation (muP) learning rate for ADAM. I did a short write up: tinyurl.com/mup-for-adam. Thanks Ilia Badanin and Eugene Golikov for your help on this.
tinyurl.com
Notion – The all-in-one workspace for your notes, tasks, wikis, and databases.
A new tool that blends your everyday work apps into one. It's the all-in-one workspace for you and your team
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