AI Briefing#vision-language-model
The latest AI and developer news about #vision-language-model, with the original source and a short summary.
The latest AI and developer news about #vision-language-model, with the original source and a short summary.
LAVE is proposed as a metric that uses an LLM to evaluate semantic similarity instead of the existing string-matching approach.
HuggingFace has released Docmatix, a DocVQA dataset that is 240 times larger than existing ones, containing 2.4 million images and 9.5 million Q/A pairs.
Introduces how to fine-tune Microsoft's small vision-language model Florence-2 for DocVQA tasks and the resulting performance.
Google has released PaliGemma, a new open vision language model (VLM) that combines SigLIP and Gemma.
Fine-tuning BridgeTower on Habana Gaudi2 achieved 2.5x faster performance compared to A100.
Kakao Brain has open-sourced the COYO dataset, containing 700 million image-text pairs, along with ViT and ALIGN models trained on it.
BLIP-2 introduces efficient vision-language learning through a Q-Former that connects a frozen image encoder and an LLM.
This explains the core training strategies and architecture of Vision-Language Models, which combine visual and language information.