We reviewed 31 models+21 benchmarks. There's a tension between language neutrality (same results across languages) & cultural awareness (context matters differently across cultures)
We reviewed 31 models+21 benchmarks. There's a tension between language neutrality (same results across languages) & cultural awareness (context matters differently across cultures)
by @andrei-a-manea.bsky.social & @jlibovicky.bsky.social
TL;DR: Explore how parallel datasets improve cross-lingual transfer in vision-language models. arxiv.org/abs/2504.21681
by @andrei-a-manea.bsky.social & @jlibovicky.bsky.social
TL;DR: Explore how parallel datasets improve cross-lingual transfer in vision-language models. arxiv.org/abs/2504.21681
#NLP #ComputationalLinguistics #CzechNLP #MachineLearning
#NLP #ComputationalLinguistics #CzechNLP #MachineLearning
by @jlibovicky.bsky.social , @jindrahelcl.bsky.social, @andrei-a-manea.bsky.social
Question that foreigners don't know the answer to + human judgment on question generation
Find out what your model knows about Czechia 🇨🇿, Slovakia 🇸🇰, and Ukraine 🇺🇦!
👉 Textual and visual questions, answers, and human judgment on model outputs!
huggingface.co/datasets/ufa...
www.arxiv.org/abs/2507.22752