📢I'm organizing a BoF session at #EACL2026 called Tokenization & Beyond, aiming to gather researchers exploring tokenization and alternatives such as byte-level and pixel-based approaches. Sign up using the form if you're interested! #NLProc @eaclmeeting.bsky.social

I have been thinking about some of the consequences of closed vs open research. Closed research can slow down scientific progress and concentrate knowledge, which results in what I call “model archaeology”. I discuss this idea in my ICLR 2026 Blogpost. Short thread 🧵and link👇

Announcing our latest paper: CommonLID In collaboration with @commoncrawl.bsky.social @mlcommons.org @jhu.edu we built a LID benchmark on actual Common Crawl text covering 109 languages. Existing evaluations overestimate how well LangID works on web data. arxiv.org/abs/2601.18026

Our paper on ✨populism✨ and how LLMs struggle to detect it in political debates 🗣️ has been accepted to EACL main conference. Meet the lead author @kiddothe2b.bsky.social in Rabat to discuss PolSci🤝NLP

📢 I am hiring a highly-motivated Ph.D student at the University of Copenhagen to work on tokenization-free NLP. Read our previous work in this topic: aclanthology.org/2025.emnlp-m... aclanthology.org/2023.emnlp-m... openreview.net/forum?id=FkS... Apply by March 8: employment.ku.dk/phd/?show=1563

New EACL paper (with @mdlhx.bsky.social)! We tested if comparing perplexity of parallel data across languages is fair. Turns out: it depends. We show the choice of test set (even with consistent meaning) can flip conclusions about which language is easier to model. Paper: arxiv.org/abs/2601.10580

Our paper has been accepted to EACL 2026!🎉 We systematically evaluate several vision-language (VLMs) and language-only models, measuring their alignment with brain responses to concept words. Our results show that vision-language models offer a promising tool to model human concept processing

Excited to share that 📏 Cetvel benchmark has been accepted to #EACL2026! 📏 Cetvel is designed to evaluate LLMs in Turkish. Please see the thread below for more details. #NLProc

This week, it was our pleasure to welcome @ilkerkesen.bsky.social, who shared some of his and his group's latest findings with our group. It shows how multimodal learning can help models transcend the boundaries of writing systems. We enjoyed İlker's company and look forward to his future work!

This week I’m in Utrecht! I’m visiting Utrecht University to give an invited seminar talk on pixel language models, hosted by the NLP Research Group led by Albert Gatt. Note: Don’t be fooled by the image; the weather is cloudy as expected! #NLProc

This week, I'm attending #EurIPS here in Copenhagen, where I'll present our work on pretraining a multilingual pixel language model at the #ELLIS UnConference. Find me tomorrow at 4 pm in the poster session at stand no. 59 to learn more about multilingual pixel language models.

I'm forcing GPT-5.1 to translate some English text to some target language that I don't know. It decides to use its thinking feature, and then reasons about switching to the target language for the entire output, including explanations and conversational parts. Sigh.

This week at #EMNLP2025, I'll present our research on pretraining a multilingual pixel language model. Join the multilinguality session on Friday at 10:30 in Room A301 to learn more about pixel models and their benefits in multilingual settings. (Unfortunately I’ll be on Zoom)

When is a language hard to model? Previous research has suggested that morphological complexity both does and does not play a role, but it does so by relating the performance of language models to corpus statistics of words or subword tokens in isolation.

📢New preprint: We introduce 📏Cetvel, a unified benchmark for evaluating language understanding, generation, and cultural capacity of LLMs in Turkish🇹🇷 #AI #LLM #NLProc Joint work with Abrek Er, @gozdegulsahin.bsky.social, @aykuterdem.bsky.social from KUIS AI Center.

Excited to share that our paper "Multilingual Pretraining for Pixel Language Models" has been accepted to the #EMNLP2025 main conference! Please see the thread below and the paper itself for more details.

Announcing our recent work “Multilingual Pretraining for Pixel Language Models”! We introduce PIXEL-M4, a pixel language model pretrained on four visually & linguistically diverse scripts: English, Hindi, Ukrainian & Simplified Chinese. #NLProc

Today we are releasing Kaleidoscope 🎉 A comprehensive multimodal & multilingual benchmark for VLMs! It contains real questions from exams in different languages. 🌍 20,911 questions and 18 languages 📚 14 subjects (STEM → Humanities) 📸 55% multimodal questions