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