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Found 2 papers, 1 papers with code
Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models
This report describes the training dataset creation and recipe behind the family of \texttt{arctic-embed} text embedding models (a set of five models ranging from 22 to 334 million parameters with weights open-sourced under an Apache-2 license).
Assessing the Quality of the Datasets by Identifying Mislabeled Samples
Therefore, by identifying the outliers in the latent space, we can find the mislabeled samples.
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