https://weaviate.io/blog/hybrid-search-explained 搜索可以用 hybrid: 一個向量搜尋 + 一個BM25 兩種融合方式 - Relative Score Fusion: an alpha term between 0 and 1 weighing dense vector similarity w/ sparse vector similarity - Reciprocal Rank Fusion: add 1/rank in the ranked list for both sparse and dense retrieval. 跟 [[Ensemble Retriever]] 其實一樣 只是 Hybrid Search 通常指直接用 Vector Store 提供的 Hybrid Search 功能 Ensemble Retriever 是自幹 e.g. https://python.langchain.com/docs/integrations/retrievers/weaviate-hybrid 介紹文章: https://towardsdatascience.com/improving-retrieval-performance-in-rag-pipelines-with-hybrid-search-c75203c2f2f5#f7da llamaindex 的 Qdrant Hybrid Search 範例 https://twitter.com/jerryjliu0/status/1738583302481842339 ## LlamaIndex：在RAG中通過Alpha調整增強混合檢索的檢索性能 https://www.llamaindex.ai/blog/llamaindex-enhancing-retrieval-performance-with-alpha-tuning-in-hybrid-search-in-rag-135d0c9b8a00 https://twitter.com/llama_index/status/1763252392639042024