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cs.CV2025
Synthetic Document Question Answering in Hungarian
Jonathan Li, Zoltan Csaki, Nidhi Hiremath +4
Modern VLMs have achieved near-saturation accuracy in English document visual question-answering (VQA). However, this task remains challenging in lower resource languages due to a…
cs.CV2024
BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions
Anas Awadalla, Le Xue, Manli Shu +13
We introduce BLIP3-KALE, a dataset of 218 million image-text pairs that bridges the gap between descriptive synthetic captions and factual web-scale alt-text. KALE augments synthet…
cs.CV2024
MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens
Anas Awadalla, Le Xue, Oscar Lo +11
Multimodal interleaved datasets featuring free-form interleaved sequences of images and text are crucial for training frontier large multimodal models (LMMs). Despite the rapid pro…