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We recently tested public LVLMs for fine-grained object classification (arxiv.org/abs/2406.14496). Models pretraining with >1B examples crushed it compared to LLaVA & co. PaliGemma was excellent, too, despite its size and this part of the report explains now why.

Awesome work! I don't know why but it feels strange to see my University logo in the same figure as these big labs & groups😅

Excited to present NLLB-LLM2Vec at EMNLP 2025 Tuesday 2pm! Drop by our poster to chat about multilingual & multimodal research. NLLB-LLM2Vec can now easily be used with Hugging Face AutoModels — try it esp. for embedding low-resource languages! 🌐 huggingface.co/fdschmidt93/NL…

📣Happy to (pre-)release my Fleurs-SLU benchmark to evaluate massively multilingual spoken language understanding on SIB & Belebele. Work done at Mila - Institut québécois d'IA with David Ifeoluwa Adelani 🇳🇬 Goran Glavaš Ivan Vulić Datasets: huggingface.co/datasets/WueNL… huggingface.co/datasets/WueNL… Details to follow👇

Thanks to a GPU grant by Hugging Face , you can try out Centurio Aya here: huggingface.co/spaces/WueNLP/… (code shamelessly adapted from merve demo of Llava-Next)

Introducing MVL-SIB, a massively multilingual vision-language benchmark for cross-modal topic matching in 205 languages! 🤔Tasks: Given images (sentences), select topically matching sentence (image). Arxiv: arxiv.org/abs/2502.12852 HF: huggingface.co/datasets/WueNL… Details👇