Category:
Category:
Reranking
Category:
Retrieval & RAG
Definition
Reordering retrieved results to optimize relevance before sending to an LLM.
Explanation
Reranking improves retrieval by using cross-encoders or LLM-based ranking models. It helps ensure only the most relevant chunks are passed into the context window. Reranking is essential for high-accuracy RAG pipelines and grounding-sensitive tasks like legal QA, research workflows, and analytics agents.
Technical Architecture
Top-K Retrieved Docs → Reranker (Cross Encoder or LLM) → Ranked List → Context Packager → LLM
Core Component
Cross-encoder model, LLM reranking, metadata filters, scoring heuristics
Use Cases
Search, RAG pipelines, enterprise QA, analytics
Pitfalls
Latency overhead, cost due to LLM reranking, mis-ranked results
LLM Keywords
Reranking, Cross-encoder Ranking, Retrieval Optimization
Related Concepts
Related Frameworks
• Vector Search
• Hybrid Retrieval
• Chunking
• Retrieval Optimization Framework