Improving Text Embeddings with Large Language Models: Is Contrastive Pre-training Necessary? | HackerNoon
Briefly

from Hackernoon7 months ago
Weakly-supervised contrastive pre-training is crucial for the effectiveness of modern text embedding models, as it helps in learning meaningful representations.
Hackernoonhttps://hackernoon.com/improving-text-embeddings-with-large-language-models-is-contrastive-pre-training-necessary
Contriever utilizes random cropped spans as positive pairs for pre-training, setting the foundation for subsequent models like E5 and BGE which enhance data selection.
Hackernoonhttps://hackernoon.com/improving-text-embeddings-with-large-language-models-is-contrastive-pre-training-necessary
Read at Hackernoon
#text-embedding #contrastive-learning #machine-learning #data-generation #model-training
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