Asst. Prof. in CS at @BU_Tweets ≡ {Mechanistic, causal} {interpretability, NLP}

Boston
Joined September 2015
I'm at #EMNLP2026 in Budapest! 🇭🇺 Come check out the cool work from our students, and come find me at the tutorials and workshops! More details and pretty posters for each paper below: 🧵
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Is it possible that LLMs can represent biases without verbalizing them? Using steering vectors, we find evidence from QA and hiring task settings that this is possible. Do chat with Keren online!
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Also, if you're interested in how we can make interpretability into a more rigorous science, do stop by our tutorial on Wednesday!
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Congrats to those with accepted NeurIPS papers! If you have work on vision-language modeling or egocentric learning, consider submitting your paper to the BabyVLM Workshop fast track by Sep. 27 AoE (end of the weekend). See the website for more details: babyvlm.github.io/#fast-trac…
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Aaron Mueller retweeted
New paper! 🫡 We introduce Matryoshka Attribution, a new attribution method which uses gradient descent to find which parts of a neural network are responsible for a behaviour. MAttr is #1 on the Mechanistic Interpretability Benchmark by a wide margin (2.9× the runner up).
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Aaron Mueller retweeted
**new paper: Superposition in Brains** What if Barlow was wrong? In his neuron doctrine (1972), he suggested to search for the 'trigger features' of each neuron to understand cortex. But what if that is the wrong coordinate system to understand neural representations? biorxiv.org/content/10.64898…
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Aaron Mueller retweeted
Take a break from reading up on Navier-Stokes drama and add October 29th to your calendar, as we have a stellar lineup of speakers at this years' BlackboxNLP!
🎉 Thrilled to announce the keynote speakers for BlackboxNLP 2026 @emnlpmeeting, with three incredible perspectives on interpretability: 🔍 Ivan Titov @iatitov 🔍 Sheridan Feucht @sheridan_feucht 🔍 Michael Hahn @mhahn29 Join us on October 29th! 🇭🇺
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Aaron Mueller retweeted
Submit to BabyVLM @NeurIPSConf : babyvlm.github.io/ We welcome work on: 🧠 Sample-efficient learning 👀 Vision + language 🌍 Grounded learning 👶 Developmental learning 📏 Human-inspired evaluation 🤖 Learning from limited data 📅 Deadline: August 31
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Aaron Mueller retweeted
📢 Excited to share our #EMNLP2026 Main paper, co-led by @yukyunglee_ and me! 🎉 AI-generated text shows a consistent stylometric footprint across models and domains, while AI-edited text shows a different pattern. 🔗Paper: arxiv.org/pdf/2608.27855
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Aaron Mueller retweeted
🤖🧠NEW PAPER🧠🤖 (The result of an 8-year project!) LLMs seem very different from symbolic systems. Yet LLMs excel in symbolic domains (e.g., language/code/math). How do they do it? Our finding: LLM representations have implicit symbolic structure! Link in thread ⬇️ 1/n
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Aaron Mueller retweeted
Since many are starting grad school soon, let me re-share my One Big Tip™️ for research! Research involves many skills - collaborating, writing, presenting, etc. But many of these skills can be unified under a single overarching ability: theory of mind Blog post link in reply
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NEMI workshop is starting now! Couldn’t make it to Boston? Check out the livestream on our website
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Aaron Mueller retweeted
I've been unsettled lately. Reading messages or papers feels like dissociating. Everything seems a bit alien, even if it's completely human. I've had a realization: When our simulations finally exited the Uncanny Valley, they brought the Uncanny with them. nsaphra.net/post/uncanny/
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🚨 NEMI decisions are out! Be sure to check your spam folder for the decision email, as a few have ended up there. Looking forward to seeing you at NEMI! 🎉
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Have enjoyed using Silico! We gave it descriptions of relatively complex translation/interpretability experiments, and it found simpler ways to get evidence before working through it end-to-end. Saved me and a student a lot of time iterating. I then gave @divapp213 the reins...
Silico, the platform for ambitious AI research, is publicly available today. AI is advancing fast. The tools to understand it need to advance even faster. Silico lets you interpret and train your models at frontier scale. Learn more + get access 🧵
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Divya is looking into how best to find representations of many kinds of multinomial concepts. It’s a big search space, but starting with these quick prototypes and visuals has made it easier to test more ambitious methods before getting into the weeds. xitter.cf/divapp213/status/20847…
Silico has been great for poking around model internals.
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Tired of writing NeurIPS rebuttals? Take a break by registering to attend the New England Mechanistic Interpretability workshop (deadline today)!
The NEMI workshop registration deadline is today, July 27th! Last chance to sign up to meet New England’s mech interp community, including Rhett the Terrier, who’s using J-Space to learn what LLMs think when he begs them for treats. Link in thread 👇
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The Red Sox just closed a 15-game winning streak! If your research is also smashing records, submit an abstract to the New England Mechanistic Interpretability Workshop by Aug 1!
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