“Dimicillin” isn’t real. We made it up. Yet many LLMs still call it an antibiotic. Across 9 models and 653 drugs, we find that drug-name affixes alone can drive pharmacological reasoning. Models often rely on morphology over facts. We trace this shortcut from behavior to mechanism. 🧵

Surgically editing prompts to vary a factor of interest (like gender) is an intuitive way of analyzing model behavior and sensitivity. But @zihaogavinyang.bsky.social shows that we should really compare the results from such perturbations to those observed when, e.g., we simply paraphrase inputs 👇

Zihao (Gavin) Yang@zihaogavinyang.bsky.social · 3mo ago

1/ (New paper!) If swapping the gender in an input prompt makes the AI model give a different answer it means that it has to have a gender bias, right? Wrong. 🧵 on counterfactual prompting for LLM evals: Paper: arxiv.org/abs/2605.01048

Patients ask LLMs medical questions — but how they phrase it matters more than it should. Our new preprint explores how different phrasings of patient health questions can lead to inconsistent conclusions, even with the same evidence. [1/6] Full Paper: arxiv.org/abs/2604.05051

Our ICML 2025 workshop on Actionable Interpretability drew massive interest. But the same questions kept coming up: What does "actionable" mean? Is it achievable? How? We're ready to answer. 🧵

Can you solve this algebra puzzle? 🧩 cb=c, ac=b, ab=? A small transformer can learn to solve problems like this! And since the letters don't have inherent meaning, this lets us study how context alone imparts meaning. Here's what we found:🧵⬇️

Hello world 👋 My first paper at UT Austin! We ask: what happens when medical “evidence” fed into an LLM is wrong? Should your AI stay faithful, or should it play it safe when the evidence is harmful? We show that frontier LLMs accept counterfactual medical evidence at face value.🧵

Check out @hibaahsan.bsky.social's paper on spotting (problematic) racial biases in LLMs for healthcare applications 👇

Hiba Ahsan@hibaahsan.bsky.social · 9mo ago

LLMs have been shown to provide different predictions in clinical tasks when patient race is altered. Can SAEs spot this undue reliance on race? 🧵 Work w/ @byron.bsky.social Link: arxiv.org/abs/2511.00177

3/ 🏥 A separate team at Northeastern located where certain signals live inside Olmo and made targeted edits that reduced biased clinical predictions. This kind of audit is only possible because Olmo exposes all its components. → buff.ly/HkChr4Q

Chantal (and Vinith) find that you can jailbreak LLMs with syntax! Some examples: cshaib.github.io/syntax_domai...

Chantal@chantalsh.bsky.social · 10mo ago

Syntax that spuriously correlates with safe domains can jailbreak LLMs - e.g. below with GPT4o mini Our paper (co w/ Vinith Suriyakumar) on syntax-domain spurious correlations will appear at #NeurIPS2025 as a ✨spotlight! + @marzyehghassemi.bsky.social, @byron.bsky.social, Levent Sagun

Now to appear at #EMNLP2025 (Findings). We've added more models and experiments: arxiv.org/abs/2502.13319

Hiba Ahsan@hibaahsan.bsky.social · last yr.

LLMs are known to perpetuate social biases in clinical tasks. Can we locate and intervene upon LLM activations that encode patient demographics like gender and race? 🧵 Work w/ @arnabsensharma.bsky.social, @silvioamir.bsky.social, @davidbau.bsky.social, @byron.bsky.social arxiv.org/abs/2502.13319

Can we distill *circuits* from teacher models into smaller students? 👇

Somin W@sominw.bsky.social · 10mo ago

🔊 New work w/ @silvioamir.bsky.social & @byron.bsky.social! We show you can distill a model’s mechanism, not just its answers -- teaching a small LM to run it's circuit same as a larger teacher model. We call it Circuit Distillation. (1/4)

Who is going to be at #COLM2025? I want to draw your attention to a COLM paper by my student @sfeucht.bsky.social that has totally changed the way I think and teach about LLM representations. The work is worth knowing. And you can meet Sheridan at COLM, Oct 7! bsky.app/profile/sfe...

Can we quantify what makes some text read like AI "slop"? We tried 👇

Chantal@chantalsh.bsky.social · 11mo ago

"AI slop" seems to be everywhere, but what exactly makes text feel like "slop"? In our new work (w/ @tuhinchakr.bsky.social, Diego Garcia-Olano, @byron.bsky.social ) we provide a systematic attempt at measuring AI "slop" in text! arxiv.org/abs/2509.19163 🧵 (1/7)

Our new paper asks: what is the goal of “natural language verbalization” interpretability approaches? If a verbalizer is supposed to tell us something about what’s in the target LM and NOT just what’s in the verbalizer LM, how do we actually evaluate that?

Millicent Li@millicentli.bsky.social · 11mo ago

In short: Verbalizer evals are broken! To know what info a model REMOVES from input, reconstruction is better than verbalization. And verbalization tells very little about what a model ADDS to input! w/A. Ceballos, G. Rogers, @nsaphra.bsky.social @byron.bsky.social 8/8

Wouldn’t it be great to have questions about LM internals answered in plain English? That’s the promise of verbalization interpretability. Unfortunately, our new paper shows that evaluating these methods is nuanced—and verbalizers might not tell us what we hope they do. 🧵👇1/8

Thrilled to share our research showing how LLM models can be influenced by bias from "spun" medical literature is now featured in Northeastern's Khoury news! This shows critical insights as AI enters healthcare. The full paper can be found at arxiv.org/abs/2502.07963

As AI expands into medicine, Northeastern study finds AI models influenced by medical bias  - Khoury College of Computer Sciences

Humans can be easily influenced by language that is one-sided, especially in complex fields like medicine. But a new Khoury-led study shows that large language models, too, can be tricked […]

khoury.northeastern.edu

This Friday NEMI 2025 is at Northeastern in Boston, 8 talks, 24 roundtables, 90 posters; 200+ attendees. Thanks to goodfire.ai/ for sponsoring! nemiconf.github.io/summer25/ If you can't make it in person, the livestream will be here: www.youtube.com/live/4BJBis...

New England Mechanistic Interpretability Workshop

About:The New England Mechanistic Interpretability (NEMI) workshop aims to bring together academic and industry researchers from the New England and surround...

youtube.com

Chatted with @byron.bsky.social at icml about my recent work, so look out for his upcoming "Tokenization is More Than More Than Compression".

Are we fact-checking medical claims the right way? 🩺🤔 Probably not. In our study, even experts struggled to verify Reddit health claims using end-to-end systems. We show why—and argue fact-checking should be a dialogue, with patients in the loop arxiv.org/abs/2506.20876 🧵1/

[📄] 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! 🙏

Oxford Word of the Year 2024 - Oxford University Press

The Oxford Word of the Year 2024 is 'brain rot'. Discover more about the winner, our shortlist, and 20 years of words that reflect the world.

corp.oup.com

🌟Job ad🌟 We (@gregdnlp.bsky.social, @mattlease.bsky.social and I) are hiring a postdoc fellow within the CosmicAI Institute, to do galactic work with LLMs and generative AI! If you would like to push the frontiers of foundation models to help solve myths of the universe, please apply!

NSF-Simons AI Institute for Cosmic Origins (CosmicAI)@nsfsimonscosmicai.bsky.social · last yr.

Seeking candidates (within three years of the award of their PhD) for a postdoctoral position with the Explorable Universe research group to perform research on developing next-generation generative AI copilots & agents to aid astronomy research. Info here www.cosmicai.org/jobs/postdoc...

LLMs are known to perpetuate social biases in clinical tasks. Can we locate and intervene upon LLM activations that encode patient demographics like gender and race? 🧵 Work w/ @arnabsensharma.bsky.social, @silvioamir.bsky.social, @davidbau.bsky.social, @byron.bsky.social arxiv.org/abs/2502.13319

🚨 Do LLMs fall for spin in medical literature? 🤔 In our new preprint, we find that LLMs are susceptible to biased reporting of clinical treatment benefits in abstracts—more so than human experts. 📄🔍 [1/7] Full Paper: arxiv.org/abs/2502.07963 🧵👇

📢 Can we trace a small distilled model back to its teacher? 🤔New work (w/ @chantalsh.bsky.social, @silvioamir.bsky.social & @byron.bsky.social) finds some footprints left by LLMs in distillation! [1/6] 🔗 Full paper: arxiv.org/abs/2502.06659

Who Taught You That? Tracing Teachers in Model Distillation

Model distillation -- using outputs from a large teacher model to teach a small student model -- is a practical means of creating efficient models for a particular task. We ask: Can we identify a stud...

arxiv.org

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.

📣 🌍 We're hiring for 2 Machine Learning researchers to join SOLACE-AI @kingscollegelondon.bsky.social , funded by @wellcometrust.bsky.social . This is your chance to develop cutting-edge AI to directly impact global health responses to climate emergencies. jobs.ac.uk/job/DLM377

OLMo 2 is out 🥳 7B and 13B trained on 5T tokens, and meticulousy instruction tuned using Tulu 3 recipe. Simply the best fully open models yet. Really proud of the work & the amazing team at @ai2.bsky.social

I'll be @ #EMNLP2024 if anyone wants to find snobby coffee / despair about election / or I guess talk research. Some work to be presented👇