Test-Time Strategies for More Efficient and Accurate Agentic RAG
Retrieval-Augmented Generation (RAG) systems face challenges with complex, multihop questions, and agentic frameworks such as Search-R1 (Jin et al., 2025), which operates iteratively, have been proposed to address these complexities. However, such approaches can introduce inefficiencies, including repetitive retrieval of previously processed information and challenges in contextualizing retrieved results effectively within the current generation prompt. Such issues can lead to unnecessary retrieval turns, suboptimal reasoning, inaccurate answers, and increased token consumption. In this paper, we investigate test-time modifications to the Search-R1 pipeline to mitigate these identified sh...
| Authors | Brian Zhang, Deepti Guntur, Zhiyang Zuo et al. |
|---|---|
| Primary category | cs.IR |
| Published | 12 March 2026 |
| Last updated at source | 12 March 2026 |
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