Are Multimodal Large Language Models Good Annotators for Image Tagging?

A new paper explores the potential of Multimodal Large Language Models (MLLMs) for automating image tagging, finding they can significantly reduce annotation costs and achieve high performance in downstream tasks. The study introduces TagLLM, a framework that enhances MLLM-generated annotations to nearly match human quality, offering substantial benefits for content creators looking to streamline image tagging processes.

Read the full article at arXiv cs.CV (Vision)

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