Definition
Model Fusion is the architectural process of merging outputs from multiple retrieval strategies or diverse LLM inferences into a single prioritized result, typically using algorithms like Reciprocal Rank Fusion (RRF) to consolidate vector-based and keyword-based search results in hybrid RAG pipelines.
Distinguish from 'Model Merging' (combining weights); fusion combines outputs or ranks post-inference.
"An Olympic judging panel where multiple individual scores are aggregated into a single final standing."
- Reciprocal Rank Fusion (RRF)(Prerequisite)
- Hybrid Search(Component)
- Cross-Encoder(Related Process (Re-ranking))
Conceptual Overview
Model Fusion is the architectural process of merging outputs from multiple retrieval strategies or diverse LLM inferences into a single prioritized result, typically using algorithms like Reciprocal Rank Fusion (RRF) to consolidate vector-based and keyword-based search results in hybrid RAG pipelines.
Disambiguation
Distinguish from 'Model Merging' (combining weights); fusion combines outputs or ranks post-inference.
Visual Analog
An Olympic judging panel where multiple individual scores are aggregated into a single final standing.