Improve search results by calibrating model scoring in Elasticsearch
Learn how to leverage annotated data to calibrate semantic model scoring for better search results
Exploring depth in a 'retrieve-and-rerank' pipeline
Select an optimal re-ranking depth for your model and dataset.
Introducing Elastic Rerank: Elastic's new semantic re-ranker model
Learn about how Elastic's new re-ranker model was trained and how it performs.
What is semantic reranking and how to use it?
Introducing the concept of semantic reranking. Learn about the trade-offs using semantic reranking in search and RAG pipelines.
Evaluating search relevance part 2 - Phi-3 as relevance judge
Using the Phi-3 language model as a search relevance judge, with tips & techniques to improve the agreement with human-generated annotation.
Evaluating search relevance part 1 - The BEIR benchmark
Learn to evaluate your search system in the context of better understanding the BEIR benchmark, with tips & techniques to improve your search evaluation processes.
Evaluating scalar quantization in Elasticsearch
Learn how scalar quantization can be used to reduce the memory footprint of vector embeddings in Elasticsearch through an experiment.
RAG evaluation metrics: A journey through metrics
Explore RAG evaluation metrics like BLEU score, ROUGE score, PPL, BARTScore, and more. Discover how Elastic is evaluating RAG with UniEval.