Identifying human morals and values in language is crucial for analysing lots of human- and AI-generated text. We introduce "MoVa: Towards Generalizable Classification of Human Morals and Values" - to be presented at @emnlpmeeting.bsky.social oral session next Thu #CompSocialScience #LLMs 🧵 (1/n)

🕸️ Here’s a network showing how much different models predict each other as the author of some text!

❓ Does an LLM know thyself? 🪞 Humans pass the mirror test at ~18 months 👶 But what about LLMs? Can they recognize their own writing—or even admit authorship at all? In our new paper, we put 10 state-of-the-art models to the test. Read on 👇 1/n 🧵

In our new work, we reverse-engineer two models: a standard fine-tuned (SFT), and an implicit chain-of-thought (ICoT) model to see why models struggle with multi-digit multiplication. 👉Check out the paper here: arxiv.org/abs/2510.00184 🎉Big thanks to all my amazing collaborators!

AI can accelerate scientific discovery, but only if we get the scientist–AI interaction right. The dream of “autonomous AI scientists” is tempting: machines that generate hypotheses, run experiments, and write papers. But science isn’t just automation. cichicago.substack.com/p/the-mirage... 🧵

HR Simulator™: a game where you gaslight, deflect, and “let’s circle back” your way to victory. Every email a boss fight, every “per my last message” a critical hit… or maybe you just overplayed your hand 🫠 Can you earn Enlightened Bureaucrat status? (link below!)

🚀 We’re thrilled to announce the upcoming AI & Scientific Discovery online seminar! We have an amazing lineup of speakers. This series will dive into how AI is accelerating research, enabling breakthroughs, and shaping the future of research across disciplines. ai-scientific-discovery.github.io

As AI becomes increasingly capable of conducting analyses and following instructions, my prediction is that the role of scientists will increasingly focus on identifying and selecting important problems to work on ("selector"), and effectively evaluating analyses performed by AI ("evaluator").

We are proposing the second workshop on AI & Scientific Discovery at EACL/ACL. The workshop will explore how AI can advance scientific discovery. Please use this Google form to indicate your interest (corrected link): forms.gle/MFcdKYnckNno... More in the 🧵! Please share! #MLSky 🧠

⚡️Ever asked an LLM-as-Marilyn Monroe about the 2020 election? Our paper calls this concept incongruence, common in both AI and how humans create and reason. 🧠Read my blog to learn what we found, why it matters for AI safety and creativity, and what's next: cichicago.substack.com/p/concept-in...

Prompting is our most successful tool for exploring LLMs, but the term evokes eye-rolls and grimaces from scientists. Why? Because prompting as scientific inquiry has become conflated with prompt engineering. This is holding us back. 🧵and new paper with @ari-holtzman.bsky.social .

When you walk into the ER, you could get a doc: 1. Fresh from a week of not working 2. Tired from working too many shifts @oziadias.bsky.social has been both and thinks that they're different! But can you tell from their notes? Yes we can! Paper @natcomms.nature.com www.nature.com/articles/s41...

Humbled to receive an honorable mention🌟

Since @elenal3ai.bsky.social cannot make it, I presented the poster on concept incongruence: arxiv.org/abs/2505.14905

I am glad that you found our paper entertaining! This is a great point for my follow-up thread on the implications of concept incongruence. Our main goal is to raise awareness and provide clarity around concept incongruence.

🚨 New paper alert 🚨 Ever asked an LLM-as-Marilyn Monroe who the US president was in 2000? 🤔 Should the LLM answer at all? We call these clashes Concept Incongruence. Read on! ⬇️ 1/n 🧵

🧑‍⚖️How well can LLMs summarize complex legal documents? And can we use LLMs to evaluate? Excited to be in Albuquerque presenting our paper this afternoon at @naaclmeeting 2025!

🚀🚀🚀Excited to share our latest work: HypoBench, a systematic benchmark for evaluating LLM-based hypothesis generation methods! There is much excitement about leveraging LLMs for scientific hypothesis generation, but principled evaluations are missing - let’s dive into HypoBench together.

Encourage your students to submit posters and register! Limited free housing is provided for student participants only, on a first-come (i.e., request)-first-serve basis. We are also actively looking for sponsors. Reach out if you are interested! Please repost! Help spread the words!

1/n You may know that large language models (LLMs) can be biased in their decision-making, but ever wondered how those biases are encoded internally and whether we can surgically remove them?

New preprint! Metaphors shape how people understand politics, but measuring them (& their real-world effects) is hard. We develop a new method to measure metaphor & use it to study dehumanizing metaphor in 400K immigration tweets Link: bit.ly/4i3PGm3 #NLP #NLProc #polisky #polcom #compsocialsci 🐦🐦

Compositional representations are a key attributes of intelligent systems that generalize well. An issue is that there is no robust way to quantify compositionality. Below is our attempt at such a quantifiable measurement. arxiv.org/abs/2410.148... w/ E Elmoznino & T Jiralerspong & Y Bengio

How do everyday narratives reveal hidden cause-and-effect patterns that shape our beliefs and behaviors? In our paper, we propose Causal Micro-Narratives to uncover narratives from real-world data. As a case study, we characterize the narratives about inflation in news.