Lately, there have been significant strides in applying deep neural networks to the search field in machine learning, with a specific emphasis on representation learning within the bi-encoder architecture. In this framework, various types of content, including queries, passages, and even multimedia, such as images, are transformed into compact and meaningful “embeddings” represented as dense vectors. These dense retrieval models, built on this architecture, serve as the…
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