dali-does/vse-probing
Code for COLING2020 paper: Probing Multimodal Embeddings for Linguistic Properties.
This tool helps researchers analyze how well multimodal AI models understand linguistic concepts in images and text. It takes existing image-caption datasets (like MSCOCO) and pretrained visual-semantic embedding models as input, then runs tests to see if the models have learned properties like object categories or semantic congruence. Researchers in AI and natural language processing can use this to evaluate and compare the linguistic capabilities of different multimodal models.
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Use this if you are an AI researcher wanting to understand the linguistic knowledge captured within visual-semantic embedding models.
Not ideal if you are looking to train or deploy a new visual-semantic model, as this tool focuses on analyzing existing ones.
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Language
Python
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Apache-2.0
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Last pushed
Apr 12, 2021
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