AINeutralarXiv – CS AI · Mar 176/10
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Compute Allocation for Reasoning-Intensive Retrieval Agents
Researchers studied computational resource allocation in AI retrieval systems for long-horizon agents, finding that re-ranking stages benefit more from powerful models and deeper candidate pools than query expansion stages. The study suggests concentrating compute power on re-ranking rather than distributing it uniformly across pipeline stages for better performance.
🧠 Gemini