Lexical-Semantic Fusion

Combining multiple retrieval approaches can overcome the limitations of individual methods:

Sparse-Dense Hybrid Retrieval:

• Dense retrieval: Vector similarity captures semantic relationships
• Sparse retrieval: Keyword matching (BM25) captures exact terminology
• Hybrid approaches combine both signals for improved relevance

Reciprocal Rank Fusion (RRF):

• Merges results from multiple retrieval methods
• Weights items based on their rank in each result set
• Provides robust performance across diverse query types

ColBERT and Late-Interaction Models:

• Represent texts as sets of contextualized token embeddings
• Perform fine-grained matching between query and document terms
• Balance computational efficiency with matching precision

Fusion approaches provide robustness against the weaknesses of individual retrieval methods, handling both semantic concepts and specific terminology effectively.