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Copy file name to clipboardExpand all lines: docs/reference/reranking/semantic-reranking.asciidoc
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@@ -31,7 +31,6 @@ Semantic re-ranking enables a variety of use cases:
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* *Semantic retrieval results re-ranking*
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** Improves results from semantic retrievers using ELSER sparse vector embeddings or dense vector embeddings by using more powerful models.
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** Adds a refinement layer on top of hybrid retrieval with <<rrf, reciprocal rank fusion (RRF)>>.
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* *General applications*
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** Supports automatic and transparent chunking, eliminating the need for pre-chunking at index time.
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* Read the <<retriever,retriever reference documentation>> for syntax and implementation details
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* Learn more about the <<retrievers-overview,retrievers>> abstraction
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* Learn more about the Elastic <<inference-apis,Inference APIs>>
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* Check out our https://github.com/elastic/elasticsearch-labs/blob/main/notebooks/integrations/cohere/cohere-elasticsearch.ipynb[Python notebook] for using Cohere with {es}
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* Check out our https://github.com/elastic/elasticsearch-labs/blob/main/notebooks/integrations/cohere/cohere-elasticsearch.ipynb[Python notebook] for using Cohere with {es}
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