Hybrid IR
IR: Information Retrieval
Overview
Hybrid information retrieval studies how to combine complementary signals, especially exact-term sparse search such as BM25 and semantic dense-vector search, to find evidence that either method might miss alone. Systems may also connect search with knowledge graphs, relational databases, and source-native query engines, using rank fusion, reranking, or query routing before retrieval-augmented generation. These approaches support question answering, technical support, and search across sources where wording varies or evidence is split between documents and structured data. Fusion often improves recall and ranking, but results vary by domain; adaptive routing, fair evaluation, cross-domain transfer, and reliable evidence grounding remain open challenges.
Latest papers
18 papers1 paper in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.