Real ChatGPT answer · index seedS7yd5zUDVuwcompleteB2B software · AI and automation toolsinformational
How do we configure cross-encoder rerankers to improve the precision of initial retrieval results in our enterprise knowledge base search tool?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
How do we configure cross-encoder rerankers to improve the precision of initial retrieval results in our enterprise knowledge base search tool?
1 real search · 1 real-search pass
cross encoder reranking best practices retrieve rerank top k sentence transformers documentationGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
cross encoder reranking best practices retrieve rerank top k sentence transformers documentation Google ↗
- Quickstart · sbert.net
- Develop a RAG Solution on Azure - Information-Retrieval Phase - Azure Architecture Center · learn.microsoft.com
- sentence-transformers/docs/cross_encoder/usage/usage.rst at main · huggingface/sentence-transformers · github.com
- Cross-Encoders · sbert.net
- Training Overview · sbert.net
- Evaluation · sbert.net