Definition
The algorithmic process of re-ordering a candidate set of retrieved documents to ensure the most contextually pertinent information is positioned at the top of the context window for an LLM. It often utilizes Cross-Encoders or scoring functions to refine results, balancing the trade-off between high-latency deep semantic scoring and low-latency vector similarity retrieval.
Distinguishes 'ordering of results' from 'initial retrieval of results' (finding vs. prioritizing).
"A head chef sorting through a pile of ingredients delivered by a runner, placing the freshest and most essential ones at the front of the prep station."
- Hybrid Search(Prerequisite)
- Cross-Encoder(Component)
- Reciprocal Rank Fusion (RRF)(Method)
- Top-K Retrieval(Prerequisite)
- Lost in the Middle(Problem Mitigated)
Conceptual Overview
The algorithmic process of re-ordering a candidate set of retrieved documents to ensure the most contextually pertinent information is positioned at the top of the context window for an LLM. It often utilizes Cross-Encoders or scoring functions to refine results, balancing the trade-off between high-latency deep semantic scoring and low-latency vector similarity retrieval.
Disambiguation
Distinguishes 'ordering of results' from 'initial retrieval of results' (finding vs. prioritizing).
Visual Analog
A head chef sorting through a pile of ingredients delivered by a runner, placing the freshest and most essential ones at the front of the prep station.