AIBullisharXiv – CS AI · 14h ago6/10
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HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation
Researchers introduce HiPRAG, a training methodology that improves agentic RAG systems by using fine-grained process rewards to optimize search decisions. The approach reduces inefficient search behaviors while achieving 65-67% accuracy across QA benchmarks, demonstrating that optimizing reasoning processes yields better performance than outcome-only training.
🧠 Llama