I’m pleased to share the Second Key Update to the International AI Safety Report, which outlines how AI developers, researchers, and policymakers are approaching technical risk management for general-purpose AI systems. (1/6)

Personalization certainly needs boundaries and we show how that could look like!

Instruction tuning unlocks incredible skills in LLMs, but at a cost: they become dangerously overconfident. You face a choice: a well-calibrated base model or a capable but unreliable instruct model. What if you didn't have to choose? What if you could navigate the trade-off? (1/8)

River, Yinhong and I will all be in person and we look forward to the discussions!

See you next week at EMNLP! We will be presenting our work: Scaling Low-Resource MT via Synthetic Data Generation with LLMs 📍 Poster Session 13 📅 Fri, Nov 7, 10:30-12:00 - Hall C 📖 Check it out! arxiv.org/abs/2505.14423 @helsinki-nlp.bsky.social @cambridgenlp.bsky.social @emnlpmeeting.bsky.social

Can AI simulate human behavior? 🧠 The promise is revolutionary for science & policy. But there’s a huge "IF": Do these simulations actually reflect reality? To find out, we introduce SimBench: The first large-scale benchmark for group-level social simulation. (1/9)

Excited to share a "Key Update" from the International AI Safety Report, which I was proud to contribute to. We took a rigorous, evidence-based look at the latest AI developments. If you want a clear view of where things stand, this is a must-read. 👇

Heading to Vienna today to attend #ACL2025NLP! Let's chat if you are interested in LLM social simulation, personalization, character training and human-centered AI!

I will be at #acl2025 to present "Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals’ Subjective Text Perceptions" ✨ Huge thank you to my collaborators Jiaxin Pei @paul-rottger.bsky.social Philipp Cimiano @davidjurgens.bsky.social @dirkhovy.bsky.social 🍰 more below

Working on LLM social simulation and need data? Excited to announce our iNews paper is accepted to #ACL2025! 🥳 It's a large-scale dataset for predicting individualized affective responses to real-world, multimodal news. Paper: arxiv.org/abs/2503.03335 Data: huggingface.co/datasets/pit...

We created Approximate Likelihood Matching, a principled (and very effective) method for *cross-tokenizer distillation*! With ALM, you can create ensembles of models from different families, convert existing subword-level models to byte-level and a bunch more🧵

Ever notice how something that makes your blood boil barely registers with your friend? Our emotional reactions aren't universal at all—they're deeply personal. And AI needs to understand that. Excited to share our new paper: "iNews" 🧵 (1/8) arxiv.org/abs/2503.03335

Great work by @riverdong.bsky.social - we dug deep into existing datasets & algorithms and found quite some surprising stuff

Happy to write this News & Views piece on the recent audit showing LLMs picking up "us versus them" biases: www.nature.com/articles/s43... (Read-only version: rdcu.be/d5ovo) Check out the amazing (original) paper here: www.nature.com/articles/s43...

1/9 🧵 New paper alert (now in Nature Computational Science)! As polarisation continues to shape our world, we asked: Do social and political biases transfer to our AI? I.e. do LLMs show ingroup and outgroup bias? www.nature.com/articles/s43...

Such an amazing work in so many ways! Well done! Great to see convergent evidence that the more persona information you have about someone, the more accurate your simulation would be. aclanthology.org/2024.acl-lon... Is there a scaling law for simulation based on persona detailedness?

🚨New Preprint: "Generative language models exhibit social identity biases" Did you know LLMs mirror human-like biases, showing human-levels of ingroup solidarity & outgroup hostility? @profsanderlinden.bsky.social @steverathje.bsky.social 📄 arxiv.org/abs/2310.15819