The paper introduces a simple method for obtaining high-quality text embeddings using synthetic data and minimal training steps. The method outperforms existing approaches on text embedding benchmarks without using labeled data, and achieves state-of-the-art results when combined with labeled data.

https://arxiv.org/abs//2401.00368

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