📣📣 New paper with #JoergFriedrichs, @florianschaffner.bsky.social, @niklasstoehr.bsky.social , “Populism and governmentalism as thin-centered ideologies: Emotions and frames on social media” is out at @ejprjournal.bsky.social Read more: doi.org/10.1017/S147...

🔓What brought me into Machine Learning research is its universal applicability—pattern recognition underlies all empirical sciences and even lets you publish in top polscience journals such as EJPR: shorturl.at/8e1rF @giulianoformisano.bsky.social @florianschaffner.bsky.social and Joerg Friedrichs.

⚖️ Measuring Scalar Constructs in Social Science with LLMs with rising (and established) stars in Computational Social Science @haukelicht.bsky.social @rupak-s.bsky.social @patrickwu.bsky.social @pranavgoel.bsky.social @elliottash.bsky.social @alexanderhoyle.bsky.social arxiv.org/abs/2509.03116

Paper: arxiv.org/abs/2509.03116 Code: github.com/haukelicht/s... With: @haukelicht.bsky.social * @rupak-s.bsky.social * @patrickwu.bsky.social @pranavgoel.bsky.social @niklasstoehr.bsky.social @elliottash.bsky.social

[corrected link] LLMs are often used for text annotation in social science. In some cases, this involves placing text items on a scale: eg, 1 for liberal and 9 for conservative There are a few ways to handle this task. Which work best? Our new EMNLP paper has some answers🧵 arxiv.org/abs/2509.03116

Evaluating topic models (and document clustering methods) is hard. In fact, since our paper critiquing standard evaluation practices four years ago, there hasn't been a good replacement metric That ends today (we hope)! Our new ACL paper introduces an LLM-based evaluation protocol 🧵

🎓 I recently defended my PhD and moved from one dream team at ETH Zurich to another at DeepMind—a huge thank you to the many people who have supported me along the way!

Our paper "A Practical Method for Generating String Counterfactuals" has been accepted to the findings of NAACL 2025! a joint work with @matan-avitan.bsky.social , @yoavgo.bsky.social and Ryan Cotterell. We propose "Intervention Lens", a technique to explain intervention in natural language. (1/6)

Are LLMs biased when they write about political issues? We just released IssueBench – the largest, most realistic benchmark of its kind – to answer this question more robustly than ever before. Long 🧵with spicy results 👇

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.

mech interp: bsky.app/starter-pack... women in nlp: bsky.app/starter-pack... nlp #1: bsky.app/starter-pack... nlp #2: bsky.app/starter-pack... ml/data/tech: bsky.app/starter-pack... robotics & ai: bsky.app/starter-pack...

If you’re interested in mechanistic interpretability, I just found this starter pack and wanted to boost it (thanks for creating it @butanium.bsky.social !). Excited to have a mech interp community on bluesky 🎉 go.bsky.app/LisK3CP

Just launched a Political Comm/NLP/Text-as-Data Starter Pack. 🦋🤗 Join us and/or drop a message to be added! go.bsky.app/39MWTjg #starterpack #polsci

Trying to bring ML/NLP/etal people from ETH Zürich together. Ping me to add you. 🙂 bsky.app/starter-pack...