DivInit: Boosting Agentic Search via Diverse Query Initialization
๐กLearn how to improve agentic search accuracy by 5-7 points without training, using a simple query diversification hack.
โก 30-Second TL;DR
What Changed
Standard parallel sampling suffers from query redundancy at the first turn.
Why It Matters
This method provides a cost-effective way to improve agentic search accuracy without requiring additional model training. It offers a practical optimization for developers building RAG-based agent systems.
What To Do Next
Integrate DivInit into your agentic search pipeline by implementing a diversity-based selection step for initial queries to reduce retrieval overlap.
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Original source: ArXiv AI โ